DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Remark(s)
Applicant's amendment filed on June 24th, 2026 have been fully entered and considered. Applicant’s amendment to the claims have overcome each and every 103 rejection, previously set forth in the Non-Final Office Action mailed on March 25th, 2026, all new grounds of rejection set forth in the present action were necessitated by Applicants’ claim amendments. Regarding the 101 rejection, the examiner respectfully finds the amendment to still be 101 ineligible, no specific argument was given from the Applicants in the Applicants’ remarks regarding the 101 rejection, see Response to Remarks section below. Accordingly, this action is made final.
Status of Claims
Claims 1-16 are pending, claims 1-3, 6 and 8 have has been amended. Claims 1-16 remains rejected.
Response to Argument(s)
Regarding the 101 rejection:
In page 12 of the Applicants’ remarks, the Applicants state that the amendment has followed the examiner’s suggestion to overcome the 101 rejection and that for the reasons presented in the interview and without acquiescing in the examiner’s rejection, independent claims 1 and 8, as amended, and the corresponding dependent claims are 101 eligible.
Examiner’s reply:
The examiner respectfully finds the amendment to not fully follow the examiner’s suggestion during the interview conducted as indicated in the interview summary mailed on June 25th, 2026, wherein the examiner recognizes the Applicants have amended the independent claims to clarify some important claim limitations, however, as stated in the interview summary, the Applicants were suggested to further amend and focus on the image analysis part of the claim so that the claims don’t simply reflect steps of mathematical operations and concepts and activities that the human mind can perform using pen and paper, particularly how the claimed set of features are being analyzed and processed, how does the image processing system in Fig. 1D of the instant specification, filed on February 28th, 2026, process the features of the image to determine that object viewed in the augmented reality corresponds to an item through a searching and matching process, and how does the result of an indication of whether the actual value associated with the object satisfied the value condition (the last limitation of the independent claims) contribute to a practical application or improvement to an augmented reality?
The Applicants are also reminded that the claims are construed based on BRI (broadest reasonable interpretation), as for the current amendment, the independent claims 1 and 8, each merely recite steps of mathematical operations and mental process abstract ideas such as “detect a set of features included in the set of images, wherein the set of features includes different features of the object” to be a mental process wherein a human mind can observe an image and detect an object in the image and further detect its features such as color, shapes, etc., and for the limitation of “determine, based on at least one detected feature of the set of features, that the object corresponds to the item in the list of items” to be a mental process activity wherein the human mind can also observe the features of the object in the image and compare and match to see if the object corresponds to an item in an already given observable list of items, moreover for the limitation of “identify, based on the set of features, one or more noncorresponding characteristics, wherein the one or more noncorresponding characteristics are one or more expected characteristics, of the expected characteristics, that do not correspond to the features of the object” to be a mental process wherein, the human mind can observe the features and identify further characteristics of the features according to some requirements of search or condition to be met, and moreover, for the limitation of “select one or more detected features, of the set of features, associated with the one or more noncorresponding characteristics based on the expected value associated with the item and one or more values associate with the one or more noncorresponding characteristics” to be a mental process activity wherein, the human mind can observe the given data/information and some required conditions to be met and select corresponding features that met the requirements, similarly for the limitations of “determine, base don’t the selected one or more detected features, an actual value associated with the object; determine whether the actual value associated with the object satisfies a value…associated with the object” are all steps that the human mind can also perform by observing some information/data and some observable conditions to be met for the data and determine data that met the conditions.
The other limitations of “a system for….one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: obtain item-specific data that indicates an expected value and expected characteristics associated with an item in a list of items…receive….images are of an object and provide an indication of whether the actual value…satisfied the value condition” are all additional elements, under Step 2A, Prong 2, and Step 2B, of generic computer and computer components performing generic functions and steps of extra-solution activities of data gathering/receiving data/information, obtaining data/information for further processing and a post-solution activity of data outputting of indicating information/data being, providing data/information.
Hence, claims 1-16 are not 101 eligible.
Regarding the 103 prior art rejection:
In view of the Amendments to independent claims 1 and 8 the previously applied prior art rejections are withdrawn since the amendment has added new features into the claims and narrowed down the scope of the claims. Applicants’ arguments are rendered moot in view of the new grounds of rejection set forth below. See 103 rejection section below for more details.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-16 are rejected under 35 U.S.C. 101
Regarding Independent Claim 1 and its dependent claims 2-7,
Step 1 Analysis: Claim 1 is directed to a system/device, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 1 recites, in part:
“detect a set of features included in the set of images, wherein the set of features includes different features of the object;
determine, based on at least one detected feature of the set of features, that the object corresponds to the item in the list of items;
identify, based on the set of features, one or more noncorresponding characteristics, wherein the one or more noncorresponding characteristics are one or more expected characteristics, of the expected characteristics, that do not correspond to the features of the object;
select one or more detected features, of the set of features, associated with the one or more noncorresponding characteristics based on the expected value associated with the item and one or more values associated with the one or more noncorresponding characteristics;
determine, based on the selected one or more detected features, an actual value associated with the object;
determine whether the actual value associated with the object satisfies a value condition that is based on a difference between the expected value associated with the item and the actual value associated with the object.”
The limitations as mentioned as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes” grouping of abstract ideas. The limitations of:
“detect a set of features….includes different features of the object” is a step, based on BRI (broadest reasonable interpretation), a human mind can perform through a process of observation and evaluation such as, to observe images and detect features according to certain condition; “determine, based on at least one detected feature…..corresponds to the item in the list of items” is a step, based on BRI (broadest reasonable interpretation), a human mind can perform through a process of observation and evaluation such as, to observe the detected features already found and given and determine a correspondence of an object according to a condition; “identify, based on the set of features, one or more noncorresponding characteristics, wherein the one or more noncorresponding characteristics are one or more expected characteristics, of the expected characteristics, that do not correspond to the features of the object” to be a mental process wherein, the human mind can observe the features and identify further characteristics of the features according to some requirements of search or condition to be met; “select one or more detected features…..expected value associated with the item” is a step, based on BRI (broadest reasonable interpretation), a human mind can perform through a process of observation and evaluation such as, to observe a set of features already given and select more features according to a condition; “determine….an actual value….” is a step, based on BRI (broadest reasonable interpretation), a human mind can perform through a process of observation and evaluation such as, to determine an output based on observing some data according to a condition/rule; “determine whether the actual value associated….and the actual value associated with the object” is a step, based on BRI (broadest reasonable interpretation), a human mind can perform through a process of observation and evaluation such as, to determine an output based on observing some data according to a condition/rule such as recited in the claimed limitation.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. particular, the claim recites the following additional element(s) –
A system for verifying item-specific data based on data captured by an augmented reality device, the system comprising:
one or more memories; and
one or more processors, communicatively coupled to the one or more memories, configured to:
obtain item-specific data that indicates an expected value associated and expected characteristics with an item in a list of items;
receive a set of images captured by the augmented reality device, wherein the images in the set of images are of an object; and
provide an indication of whether the actual value associated with the object satisfies the value condition.
The additional elements as mentioned above include a generic system of a computer and computer components recited at high level of generality to perform generic well-known functions such as a computer to perform processing includes memories to store instructions to be executed by processors, and further additional elements of insignificant extra-solution activities of data gathering such as obtaining data/information, receiving and providing data/information, with further specification to recite what the data/information are still just merely, data/information gathering. The claim as a whole is directed to an abstract idea. Accordingly, these additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Please see MPEP §2106.04.(d).III.C.
Step 2B Analysis: the additional elements as discussed above being generic and insignificant, therefore, there are no additional elements that amount to significantly more than the judicial exception. Please see MPEP §2106.05. The claim is directed to an abstract idea.
For all of the foregoing reasons, claim 1 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 2-7 do not provide elements that overcome the deficiencies of the independent claim 1. Moreover, claim 2 recites, in part, “wherein expected characteristics…..detected features” is just a limitation of further specify what the data/information of the characteristics are to be of hence, still merely a step of data gathering insignificant extra-solution activity, post-solution activity of what the data/information are expected to be of as outcome; and the step of “provide an indication…..” is also an additional element of extra-solution activity of data gathering of providing data/information. Claim 3 recites, in part, “determine…noncorresponding characteristics” is a step of mental process, based on BRI, such as the human mind can observe data/information and determine further data/information from them according to a certain condition with pen and pencil; “provide…..” is also an additional element of extra-solution activity of data gathering of providing data/information. Claim 4 recites, in part, “determine….” is a step of mental process, based on BRI, such as the human mind can observe data/information and determine further data/information from them according to a certain condition with pen and pencil; “provide…..” is also an additional element of extra-solution activity of data gathering of providing data/information. Claim 5 recites, in part, “wherein the value condition is that….satisfies a threshold” is a limitation of giving further specification of what a condition to be of and further specification of the data/information to be of hence, still merely an abstract idea and/or data gathering step being insignificant; “identify” is a step of mental process, based on BRI, such as the human mind can observe data/information and identify further data/information from them according to a certain condition with pen and pencil; “provide…..” is also an additional element of extra-solution activity of data gathering of providing data/information. Claim 6 recites, in part, “wherein the expected characteristics….detected features” is just a limitation of further specify what the data/information of the characteristics are to be of hence, still merely a step of data gathering insignificant extra-solution activity, post-solution activity of what the data/information correspond to as outcome; “select….determine….determine….select” are steps of mental processes, based on BRI, such as the human mind can observe data/information and determine and/or identify, select further data/information from them according to a certain condition with pen and pencil. Claim 7 recites, in part, the steps of “determine….”are steps of mental processes, based on BRI, such as the human mind can observe data/information and determine further data/information from them according to a certain condition with pen and pencil, the step of “perform a search….” is a mental process wherein the human mind can perform a search according to a certain condition.
Accordingly, the dependent claims 2-7 are not patent eligible under 101.
Regarding the independent claim 8 and its dependent claims 9-16:
Step 1 Analysis: Claim 8 is directed to a method/process, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 8 recites, in part:
“detecting, a plurality of features included in the set of images, wherein the plurality of features includes different features of an object;
Identifying an item from a list of items, that corresponds to the object based on at least one feature of the plurality of features,
wherein the list of items identifies one or more characteristics that are expected to correspond to the plurality of features;
determining whether the one or more characteristics correspond to the features of the object;
identifying one or more noncorresponding characteristics of the item based on determining that the one or more characteristics do not correspond to at least one of the features of the object;
determining a noncorresponding value associated with the one or more noncorresponding characteristics; and
The limitations as mentioned as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes” grouping of abstract ideas. The limitations of:
“detecting a plurality of features included in the…..different features of the plurality of features” is a step, under BRI, a human mind can perform through a process of observation and evaluation such as, the human mind can observe set of images to evaluate and detect features includes different features of an object in the image, “identifying, from a list of items….plurality of features, wherein….the plurality of features” is a step, under BRI, a human mind can perform through a process of observation and evaluation such as, the human mind can observe set of images and the detected object to evaluate and identify an item, from a list of items according to a condition that the list of items identifies one or more characteristics correspond to the features, which the human can observe and make the determination, “determining whether….characteristics correspond to the features of the object” is a step, under BRI, a human mind can perform through a process of observation and evaluation such as, the human mind can observe the features and evaluate to determine the characteristics to correspond to the features, “identifying one or more noncorresponding characteristics….characteristics do not correspond to at least one of the features of the object” “determining a noncorresponding value….noncorresponding characteristics” is a step, under BRI, a human mind can perform through a process of observation and evaluation such as, the human mind can observe the characteristics and make an evaluation to identify the noncorresponding characteristics of the item based on another determining that the characteristics do not correspond to the features.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. particular, the claim recites the following additional element(s) –
an augmented reality device,
a system,
receiving, by a system and from the augmented reality device, a set of images captured during an augmented reality session of the augmented reality device,
providing, by the system, during the augmented reality session, an indication of the noncorresponding value associated with the one or more noncorresponding characteristics.
The additional elements include “an augmented reality device, “a system” - recited at a high level of generality (i.e. as a system recited at high level of generality to be a generic system recited as a mere attempt to implement the judicial exceptions [the mental process abstract ideas above] using a generic system; the augmented reality device being a generic recited at high level of generality device of augmented reality to perform a generic function) such that they amount to no more than mere instructions to apply the exception.
The additional elements include steps of insignificant extra-solution/post-solution activities of data gathering, data generating, data transmitting, etc. (receiving…., providing…..).
Step 2B Analysis: the additional elements as discussed above being generic and insignificant, therefore, there are no additional elements that amount to significantly more than the judicial exception. Please see MPEP §2106.05. The claim is directed to an abstract idea.
For all of the foregoing reasons, claim 8 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 9-16 do not provide elements that overcome the deficiencies of the independent claim 8. Moreover, claim 9 recites, in part, “wherein the object is associated with an initial value” is a recitation to further specify that the object is associated with an initial value hence, still abstract idea of a mere further specification of the abstract idea, “adjusting the initial value…to generate an adjusted value” is mental process step, under BRI, a human mind can observe and evaluate to adjust the initial value to generate an adjusted value using pen and paper, “providing an indication of the adjusted value” is an additional element of data gathering, data providing. Claim 10 recites, in part, “determining…noncorresponding characteristics” is a step of mental process, based on BRI, such as the human mind can observe data/information and determine further data/information from them according to a certain condition with pen and pencil; “providing…..” is also an additional element of extra-solution activity of data gathering of providing data/information. Claim 11 recites, in part, “wherein the one or more noncorresponding…..noncorresponding characteristics” is a further specification limitation hence, still abstract idea, “ranking the multiple noncorresponding….ranked noncorresponding characteristics” is a step, under BRI, a human mind can perform through a process of observation and evaluation to rank characteristics using pen and paper, “providing….” is an insignificant extra-solution activity of data gathering, data providing. Claim 12 recites, in part, ”determining whether…..satisfied a threshold” is mental process of observation and evaluation which a human mind can determine whether the noncorresponding value satisfies a threshold, “generating an alert…satisfying the threshold” is a mental process abstract idea which the human mind can observe and evaluate to generate an alert according to the observable condition as recited in the claim, “providing…” is an insignificant extra-solution activity of data gathering, data providing. Claim 13 recites, in part, “updating….noncorresponding characteristics” is a step of mental process abstract idea which the human mind can observe and evaluate to update some observable data/information such as recited in the claim, “providing…” is an insignificant extra-solution activity of data gathering, data providing. Claim 14 recites, in part, “determining a visual characteristic….one or more noncorresponding characteristics” is a mental process abstract idea which the human mind can observe and evaluate to determine visual characteristic corresponding to certain observable condition, “providing…” is an insignificant extra-solution activity of data gathering, data providing. Claim 15 recites, in part, “obtaining…” is an insignificant extra-solution activity of data gathering, data obtaining. Claim 16 recites, in part, “wherein the object is associated with an initial value” is a further specification limitation of an abstract idea, “obtaining…” is an insignificant extra-solution activity of data gathering, data obtaining, “adjusting the initial value….augmented reality device” is a mental process abstract idea which the human mind can observe and evaluate to adjust the value according to some observable condition such as recited in the claim.
For all of the foregoing reasons, claim 9-16 does not comply with the requirements of 35 USC 101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-9 and 11-16 are rejected under 35 U.S.C. 103 as being unpatentable over Chen Hu (Foreign Patent Document “CN 112884545 A” hereinafter as “Hu”) in view of Martin Enthed et. al. (“US 2023/0298050 A1” hereinafter as “Enthed”) and Chris Kalaboukis (“US 11,195,214 B1” hereinafter as “Kalaboukis”) (mapping is based on page numbers of the translation of the foreign patent document).
Regarding claim 1, Hu teaches a system for verifying item-specific data based on data captured by an augmented reality device, the system comprising (Page 1, “Background technique” section, discloses recognition or products and judging whether to purchase them based on the commodities themselves; Page 2, 4th Par., discloses “at the same time, the introduction of AR augmented reality technology”): one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to (Page 2, 3rd par., discloses the invention through a software program hence, indicates the use of a computer known to include memories, processors to execute the program): obtain item-specific data that indicates an expected value associated with an item in a list of items (Page 1, at step 5, expected price data is obtained from the user for the target product among many products); receive a set of images captured by the augmented reality device, wherein the images in the set of images are of an object (Page 1, step 1, the user scans or photographs the target product as part of an augmented reality experience [page 2, 4th par.], page 1, step 3 discloses a plurality of product images being used of the target object from photographing it from multiple angles [page 3, 3rd par.]); determine, based on the selected one or more detected features, an actual value associated with the object (Page 2, at step 6, discloses based on the input of the user and the images of the product [detected features], determine an actual device of the target product); determine whether the actual value associated with the object satisfies a value condition that is based on a difference between the expected value associated with the item and the actual value associated with the object (Page 2, at step 6, discloses determining whether the actual value of the object satisfied a value condition that the difference between the expected value and the actual value is within an established difference plan); and provide an indication of whether the actual value associated with the object satisfies the value condition (Page 2, last par., and page 3, 1st par., discloses indicating to the user if the condition is satisfied of the value condition).
However, Hu does not explicitly teach to detect a set of features included in the set of images, wherein the set of features includes different features of the object; determine, based on at least one detected feature of the set of features, that the object corresponds to the item in the list of items; select one or more detected features, of the set of features, associated with the one or more noncorresponding characteristics based on the expected value associated with the item and one or more values associated with the one or more noncorresponding characteristics.
Enthed teaches to detect a set of features included in the set of images, wherein the set of features includes different features of the object (Pars. [0110-0113] and [0124-0127], the features of the product include different features of the object being detected in the images, in order to identify the product [dynamic variables]); determine, based on at least one detected feature of the set of features, that the object corresponds to the item in the list of items (The system identify that the product in the image being identified which product it is in the data to correspond to the item in the list of items according to Pars. [0110-0113] and [0124-0127]); select one or more detected features, of the set of features, based on the expected value associated with the item (Pars. [0110-0113] and [0124-0127] discloses identifying the product in the image based on the detected features of the product in the image; the features of the product here being the recited one or more detected features of the set of features).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu of having a system for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: obtain item-specific data that indicates an expected value associated with an item in a list of items; receive a set of images captured by the augmented reality device, wherein the images in the set of images are of an object; determine, based on the one or more detected features, an actual value associated with the object; determine whether the actual value associated with the object satisfies a value condition that is based on a difference between the expected value associated with the item and the actual value associated with the object; and provide an indication of whether the actual value associated with the object satisfies the value condition, with the teachings of Enthed of having detect a set of features included in the set of images, wherein the set of features includes different features of the object; determine, based on at least one detected feature of the set of features, that the object corresponds to the item in the list of items; select one or more detected features, of the set of features, based on the expected value associated with the item.
Wherein having Hu’s system to detect a set of features included in the set of images, wherein the set of features includes different features of the object; determine, based on at least one detected feature of the set of features, that the object corresponds to the item in the list of items; select one or more detected features, of the set of features, based on the expected value associated with the item.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
However, Hu in view of Enthed do not explicitly teach to obtain item-specific data that indicates an expected value and expected characteristics; select one or more detected features, of the set of features, associated with the one or more noncorresponding characteristics based on the expected value associated with the item and one or more values associated with the one or more noncorresponding characteristics.
Kalaboukis teaches to obtain item-specific data that indicates an expected value (Col. 4, 1st Par., discloses “use the metadata to query retail computer systems to obtain current and historical data regarding a value for each item. The server computer can also run predictive analysis on a pricing model for he item and determine trends in a price for the item” indicating an expected value [item’s price]) and expected characteristics (Col. 2, last 3 Pars., disclose “create the 3D representation of the item and directly access the 3D model database and attempt to find an image on the 3D model database that matches…an image of the item can be captured by a camera on the AR deice. The image of the item can be sent to the server computer and identified by attempting to match the image with other images on the 3D model database…” wherein the 3D representation to match is analogous to the recited expected characteristics, Col.2, last Par., discloses “variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” indicating expected characteristics); select one or more detected features, of the set of features (Col.2, last Par., discloses “variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” indicating features of noncorresponding characteristics), associated with the one or more noncorresponding characteristics (Col. 2, last Par., discloses “when the item cannot be identified definitively, the individual can be presented with a plurality of images of items that come close to matching the item….variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” wherein, the non-matched data and non-matched variations being noncorresponding information as claimed) based on the expected value associated with the item (Col. 4, 1st Par., discloses “the server computer can use the metadata to query retail computer systems to obtain current and historical data regarding a value for each item. The server computer can also run predictive analysis on a pricing model for the item and determine trends in a price for the item” indicating the historical data and metadata including the matched images and associated expected values for the model to predict trends in price) and one or more values associated with the one or more noncorresponding characteristics (Col. 3, last Par., discloses “when a match is found, metadata can be obtained for the reference object that can identify an item…the metadata can indicate a name and description of the item…obtain current and historical data regarding a value for each item” indicating the matching process is to find a match for the item in the image and prices of the matches, Col.2, last Par., discloses “variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” indicating features of noncorresponding characteristics even in matches found).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Enthed of having a system for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: obtain item-specific data that indicates an expected value associated with an item in a list of items, with the teachings of Kalaboukis of having obtain item-specific data that indicates an expected value and expected characteristics; select one or more detected features, of the set of features, associated with the one or more noncorresponding characteristics based on the expected value associated with the item and one or more values associated with the one or more noncorresponding characteristics.
Wherein having Hu’s system to obtain item-specific data that indicates an expected value and expected characteristics; select one or more detected features, of the set of features, associated with the one or more noncorresponding characteristics based on the expected value associated with the item and one or more values associated with the one or more noncorresponding characteristics.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality. Since both Hu and Kalaboukis both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Kalaboukis’s system improves assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality, (see Kalaboukis’s Col. 1, 1st Par.).
Regarding claim 2, Hu in view of Enthed and Kalaboukis teach the system of claim 1, Hu teaches wherein the expected characteristics are expected to correspond to the one or more detected features (As disclosed in Hu, in page 1, last par., the expected price are expected to correspond to the item’s actual price which is determined based on detected features), and wherein the one or more processors are further configured to: provide an indication of the one or more noncorresponding characteristics (As disclosed in Hu’s page 1, last par., indicating the transaction is unsuccessful).
Regarding claim 3, Hu in view of Enthed and Kalaboukis teach the system of claim 2, Hu teaches wherein the one or more processors are further configured to: determine, based on the item-specific data, the one or more values (as disclosed in Hu’s page 1, last par., when the difference does not meet the difference plan, it is determined to confirm that the transaction is terminated and push the results to the user and show the actual price data to the user terminal and terminate the transaction [determine a value associated with the non-compliant data/noncorresponding characteristics]); and provide an indication of the one or more values. (Hu, page 1, last par., the information as discussed being provided as an indication to the user).
However, Hu in view of Enthed do not explicitly teach the one or more values being one or more values associated with the one or more values associated with the one or more noncorresponding characteristics.
Kalaboukis teaches the one or more values being one or more values associated with the one or more values associated with the one or more noncorresponding characteristics (Col. 2, last Par., discloses “when the item cannot be identified definitively, the individual can be presented with a plurality of images of items that come close to matching the item….variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” wherein, the non-matched data and non-matched variations being noncorresponding information as claimed; Col. 4, 1st Par., discloses “the server computer can use the metadata to query retail computer systems to obtain current and historical data regarding a value for each item. The server computer can also run predictive analysis on a pricing model for the item and determine trends in a price for the item” indicating the historical data and metadata including the matched images and associated expected values for the model to predict trends in price).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Enthed of having a system for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: obtain item-specific data that indicates an expected value associated with an item in a list of items; receive a set of images captured by the augmented reality device, wherein the images in the set of images are of an object; determine, based on the one or more detected features, an actual value associated with the object; determine whether the actual value associated with the object satisfies a value condition that is based on a difference between the expected value associated with the item and the actual value associated with the object; and provide an indication of whether the actual value associated with the object satisfies the value condition, with the teachings of Kalaboukis of having the one or more values being one or more values associated with the one or more values associated with the one or more noncorresponding characteristics.
Wherein having Hu’s system to the one or more values being one or more values associated with the one or more values associated with the one or more noncorresponding characteristics.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality. Since both Hu and Kalaboukis both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Kalaboukis’s system improves assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality, (see Kalaboukis’s Col. 1, 1st Par.).
Regarding claim 4, Hu in view of Enthed and Kalaboukis teach the system of claim 2, Hu teaches wherein the one or more processors are further configured to: determine a difference value based on determining that the actual value associated with the object does not satisfy the value condition; and provide an indication of the difference value (As disclosed in Hu, page 1, last par., when the difference between the expected value and the actual value does not meet the difference plan, then the system indicate to the user of the result [the difference value]).
Regarding claim 5, Hu in view of Enthed and Kalaboukis teach the system of claim 2, Hu teaches wherein the value condition is that the difference between the actual value associated with the object and the expected value associated with the item satisfies a threshold (As discussed above in claim 1 and disclosed in Hu’s page 1, last par., the difference plan is that the difference between the expected price and the actual selling price is within the difference plan threshold), and wherein the one or more processors are further configured to: identify a subset of the one or more detected features that enable the value condition to be satisfied (Page 2, 1st par., discloses the difference in step 6 refers to a plurality of artificially set differences, and the difference is fed back to the user terminal by the back-end server together with expected price data in the form of multiple coupons [a subset of one or more detected features] that enables the value condition to be satisfied); and provide an indication of the subset of the one or more detected features (Hu, page 2, last par., the coupons are being shown to the user).
Regarding claim 6, Hu in view of Enthed and Kalaboukis teach the system of claim 2, Hu teaches wherein (Page 1, at step 5, expected price data is obtained from the user for the target product among many products), wherein the expected information are expected to correspond to the one or more detected features (Hu, page 2, last par., discloses the expected price is expected to be compliant, hence the information being expected to correspond to the actual price [from detected by the system of the product and determined actual price of the product]), and wherein, to select the one or more detected features, the one or more processors are further configured to (Page 2, 3rd par., discloses the invention through a software program hence, indicates the use of a computer known to include memories, processors to execute the program): determine whether the one or more noncorresponding information includes at least one nonstandard noncorresponding characteristic (The non-compliant price is determined to not being compliant with the difference plan including set differences [Hu, page 3, 2nd par] being nonstandard noncorresponding characteristic); determine, based on determining that the one or more noncorresponding information includes the at least one nonstandard noncorresponding information, at least one nonstandard value associated with the at least one nonstandard noncorresponding information (Page 2, last par., of Hu, when its determined that the noncompliant price being the expected price not meeting the difference plan, then it’s determined that the expected price include non-compliant prices [the noncorresponding characteristic includes nonstandard noncorresponding information]); and select the one or more detected features, of the set of features (Page 2, last par., of Hu, the select the one or more detected features, of the set of features as discussed above in claim 1, now is based on the item being expected a price noncompliant with the difference plan), based on the expected value associated with the item and the at least one nonstandard value associated with the at least one nonstandard noncorresponding characteristic (that the expected value associated with item having a non-compliant price being analogous to the nonstandard value associated with the determined expected price not meeting the difference plan [nonstandard noncorresponding characteristic], according to Hu, page 2, last par.).
However, Hu in view of Enthed do not explicitly teach the one or more information being one or more characteristics, and the one or more noncorresponding information being one or more noncorresponding characteristics.
Kalaboukis teaches the one or more information being one or more characteristics (Col. 2, last 3 Pars., disclose “create the 3D representation of the item and directly access the 3D model database and attempt to find an image on the 3D model database that matches…an image of the item can be captured by a camera on the AR deice. The image of the item can be sent to the server computer and identified by attempting to match the image with other images on the 3D model database…” wherein the 3D representation to match is analogous to the recited expected characteristics, Col.2, last Par., discloses “variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” indicating expected characteristics), and the one or more noncorresponding information being one or more noncorresponding characteristics (Col. 2, last Par., discloses “when the item cannot be identified definitively, the individual can be presented with a plurality of images of items that come close to matching the item….variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” wherein, the non-matched data and non-matched variations being noncorresponding information as claimed).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Enthed of having a system for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: obtain item-specific data that indicates an expected value associated with an item in a list of items, with the teachings of Kalaboukis of having the one or more information being one or more characteristics, and the one or more noncorresponding information being one or more noncorresponding characteristics.
Wherein having Hu’s system having the one or more information being one or more characteristics, and the one or more noncorresponding information being one or more noncorresponding characteristics.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality. Since both Hu and Kalaboukis both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Kalaboukis’s system improves assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality, (see Kalaboukis’s Col. 1, 1st Par.).
Regarding claim 7, Hu in view of Enthed and Kalaboukis teach the system of claim 1.
However, Hu in view of Kalaboukis do not explicitly teach wherein, to determine that the object corresponds to the item, the one or more processors are further configured to: determine one or more visual characteristics that correspond to the at least one detected feature; perform a search using an image repository and based on the one or more visual characteristics to identify one or more aspects associated with the item; determine that the one or more aspects correspond to the at least one detected feature based on the one or more aspects including features having visual characteristics that have a threshold degree of similarity with the one or more visual characteristics; and determine that the object corresponds to the item based on determining that the one or more aspects correspond to the at least one detected feature.
Enthed teaches wherein, to determine that the object corresponds to the item, the one or more processors are further configured to: determine one or more visual characteristics that correspond to the at least one detected feature (Pars. [0123-0124] disclose detecting features in the scene and identify the produce based on the detected features); perform a search using an image repository and based on the one or more visual characteristics to identify one or more aspects associated with the item (Par. [0124] discloses the system search in the image repository [elimination of produces not matching the detected features and are not likely to be included in the catalog of furnishings for one instance] to identify the product and its features being compared against a set of rules [aspects being associated with the item]); determine that the one or more aspects correspond to the at least one detected feature (Par. [0124] the identification of the produce is being performed based on the detected features in the image and filter the objects against a set of rules) based on the one or more aspects including features having visual characteristics that have a threshold degree of similarity with the one or more visual characteristics (Par. [0126] discloses wherein the detected potential produces are analyzed by comparing the image data of the potential produces with models of sample images of the products based on a prioritization score [degree of similarity] to generate similar product arrangement for showing the virtual price tag, Par. [0112] discloses the generated similar product arrangement for showing the virtual price tag); and determine that the object corresponds to the item based on determining that the one or more aspects correspond to the at least one detected feature (And identify the products based on the processing as discussed according to Pars [0127-0128]).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a system for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Enthed of having wherein, to determine that the object corresponds to the item, the one or more processors are further configured to: determine one or more visual characteristics that correspond to the at least one detected feature; perform a search using an image repository and based on the one or more visual characteristics to identify one or more aspects associated with the item; determine that the one or more aspects correspond to the at least one detected feature based on the one or more aspects including features having visual characteristics that have a threshold degree of similarity with the one or more visual characteristics; and determine that the object corresponds to the item based on determining that the one or more aspects correspond to the at least one detected feature.
Wherein having Hu’s system to wherein, to determine that the object corresponds to the item, the one or more processors are further configured to: determine one or more visual characteristics that correspond to the at least one detected feature; perform a search using an image repository and based on the one or more visual characteristics to identify one or more aspects associated with the item; determine that the one or more aspects correspond to the at least one detected feature based on the one or more aspects including features having visual characteristics that have a threshold degree of similarity with the one or more visual characteristics; and determine that the object corresponds to the item based on determining that the one or more aspects correspond to the at least one detected feature.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Regarding claim 8, Hu teaches a method of verifying item-specific data based on data captured by an augmented reality device, comprising (Page 1, “Background technique” section, discloses recognition or products and judging whether to purchase them based on the commodities themselves): receiving, by a system and from the augmented reality device, a set of images captured during an augmented reality session of the augmented reality device (Page 2, 3rd Par., discloses the invention through a software program hence, indicates the use of a computer known to include memories, processors to execute the program; page 1, step 1, the user scans or photographs the target product as part of an augmented reality experience [Page 2, 4th Par.], page 1, step 3 discloses a plurality of product images being used of the target object from photographing it from multiple angles [Page 3, 3rd Par.]); identifying, by the system, an item, from a list of items, that corresponds to the object based on at least one feature of the plurality of features (Page 1, at step 5, expected price data is obtained from the user for the target product among many products); determining, by the system, whether the one or more characteristics correspond to the features of the object (Page 2, at step 6, discloses based on the input of the user and the images of the product [detected features], determine an actual device of the target product); identifying, by the system, one or more noncorresponding information of the item based on determining that the one or more characteristics do not correspond to at least one of the features of the object (as disclosed in Hu, in page 1, last par., the expected price are expected to correspond to the item’s actual price which); determining, by the system, a noncorresponding value associated with the one or more noncorresponding information (as disclosed in Hu, last par., the system compares to the price, when the expected price does not correspond with the difference plan, then it can be understood that the expected price is noncorresponding information), providing, by the system, an indication of the noncorresponding value associated with the one or more noncorresponding information (as disclosed in Hu’s page 1, last par., indicating the transaction is unsuccessful)
However, Hu does not explicitly disclose detecting, by the system, a plurality of features included in the set of images, wherein the plurality of features includes different features of an object; wherein the list of items identifies one or more characteristics that are expected to correspond to the plurality of features; and providing, by the system, during the augmented reality session, an indication.
Enthed teaches detecting, by the system, a plurality of features included in the set of images, wherein the plurality of features includes different features of an object (Pars. [0110-0113] and [0124-0127] discloses identifying the product in the image based on the detected features of the product in the image; the features of the product here being the recited one or more detected features of the set of features; as discussed previously and disclosed in Pars. [0110-0113] and [0124-0127], the features of the product include different features of the object being detected in the images, in order to identify the product [dynamic variables]; as discussed, then the system identify that the product in the image being identified which product it is in the data to correspond to the item in the list of items); wherein the list of items identifies one or more information that are expected to correspond to the plurality of features (The input expected price data as discussed above in claim 1 to be analogous to the recited item-specific data which indicates information associated with the item being the expected price data in form of multiple coupons [information according to page 2, 1st par.]); and providing, by the system, during the augmented reality session, an indication (Par. [0120] discloses “example user inputs in virtual reality embodiments, include a user sections of a virtual scene which may include one or more products”).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu of having a method for verifying item-specific data based on data captured by an augmented reality device, the method to obtain item-specific data that indicates an expected value associated with an item in a list of items; receive a set of images captured by the augmented reality device, wherein the images in the set of images are of an object; determine, based on the one or more detected features, an actual value associated with the object; determine whether the actual value associated with the object satisfies a value condition that is based on a difference between the expected value associated with the item and the actual value associated with the object; and provide an indication of whether the actual value associated with the object satisfies the value condition, with the teachings of Enthed of having detecting, by the system, a plurality of features included in the set of images, wherein the plurality of features includes different features of an object; wherein the list of items identifies one or more characteristics that are expected to correspond to the plurality of features; and providing, by the system, during the augmented reality session, an indication.
Wherein having Hu’s method of having detecting, by the system, a plurality of features included in the set of images, wherein the plurality of features includes different features of an object; wherein the list of items identifies one or more characteristics that are expected to correspond to the plurality of features; and providing, by the system, during the augmented reality session, in indication.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
However, Hu in view of Enthed do not explicitly teach the one or more information being one or more characteristics, and the one or more noncorresponding information being one or more noncorresponding characteristics.
Kalaboukis teaches the one or more information being one or more characteristics (Col. 2, last 3 Pars., disclose “create the 3D representation of the item and directly access the 3D model database and attempt to find an image on the 3D model database that matches…an image of the item can be captured by a camera on the AR deice. The image of the item can be sent to the server computer and identified by attempting to match the image with other images on the 3D model database…” wherein the 3D representation to match is analogous to the recited expected characteristics, Col.2, last Par., discloses “variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” indicating expected characteristics), and the one or more noncorresponding information being one or more noncorresponding characteristics (Col. 2, last Par., discloses “when the item cannot be identified definitively, the individual can be presented with a plurality of images of items that come close to matching the item….variations can be found in matching items. For example, one possible match for the item may be red, another possible match may be green” wherein, the non-matched data and non-matched variations being noncorresponding information as claimed).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Enthed of having a method for verifying item-specific data based on data captured by an augmented reality device, the method to obtain item-specific data that indicates an expected value associated with an item in a list of items; receive a set of images captured by the augmented reality device, wherein the images in the set of images are of an object; determine, based on the one or more detected features, an actual value associated with the object; determine whether the actual value associated with the object satisfies a value condition that is based on a difference between the expected value associated with the item and the actual value associated with the object; and provide an indication of whether the actual value associated with the object satisfies the value condition, with the teachings of Kalaboukis of having the one or more information being one or more characteristics, and the one or more noncorresponding information being one or more noncorresponding characteristics.
Wherein having Hu’s method having the one or more information being one or more characteristics, and the one or more noncorresponding information being one or more noncorresponding characteristics.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality. Since both Hu and Kalaboukis both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Kalaboukis’s system improves assessment of value of item by accurately obtaining and predicting prices of items based on image obtained from augmented reality, (see Kalaboukis’s Col. 1, 1st Par.).
Regarding claim 9, Hu in view of Enthed and Kalaboukis teach the method of claim 8.
However, Hu in view of Kalaboukis does not explicitly teach wherein the object is associated with an initial value; and the method further comprises: adjusting the initial value based on the noncorresponding value to generate an adjusted value; and providing an indication of the adjusted value.
Enthed teaches wherein the object is associated with an initial value (The product being given a virtual tag such as disclosed in [0166]); and the method further comprises: adjusting the initial value based on the noncorresponding value to generate an adjusted value (Par. [0167] discloses the virtual price tag can be changed or updated [adjusted as claimed]); and providing an indication of the adjusted value (as displayed to the user according to [0127]).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Enthed of having wherein the object is associated with an initial value; and the method further comprises: adjusting the initial value based on the noncorresponding value to generate an adjusted value; and providing an indication of the adjusted value.
Wherein having Hu’s method having wherein the object is associated with an initial value; and the method further comprises: adjusting the initial value based on the noncorresponding value to generate an adjusted value; and providing an indication of the adjusted value.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Regarding claim 11, Hu in view of Enthed and Kalaboukis teach the method of claim 8, Hu teaches wherein the one or more noncorresponding characteristics includes multiple noncorresponding characteristics (Wherein the non-compliant being the noncorresponding characteristic as taught in Hu, wherein when the customer since the difference plan includes a plurality of set differences according to Hu’s Page 3, 2nd Par.).
However, Hu in view of Kalaboukis do not explicitly teach wherein the multiple noncorresponding characteristics are associated with priority levels, and wherein the method further comprises: ranking the multiple noncorresponding characteristics, based on the associated priority levels, to generate ranked noncorresponding characteristics; and providing an indication of the ranked noncorresponding characteristics.
Enthed teaches wherein the multiple noncorresponding characteristics are associated with priority levels (Enthed’s Par. [0126] discloses the produces can be given priority levels for potential products for produce arrangement; the produce can be given virtual prices; since the expected values are always given to the produce by the user in Hu’s invention, in the case wherein the expected price is non-compliant [noncorresponding] or compliant, in both cases, the produces are always being identified first before even this compliance determination), and wherein the method further comprises: ranking the multiple noncorresponding characteristics, based on the associated priority levels, to generate ranked noncorresponding characteristics (Enthed’s Par. [0126] discloses the system rank the priority levels for the products based on prioritization scores for every detected product); and providing an indication of the ranked noncorresponding characteristics (Pars. [0125-127] discloses the product arrangement is given based on the prioritization).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Enthed of having wherein the multiple noncorresponding characteristics are associated with priority levels, and wherein the method further comprises: ranking the multiple noncorresponding characteristics, based on the associated priority levels, to generate ranked noncorresponding characteristics; and providing an indication of the ranked noncorresponding characteristics.
Wherein having Hu’s method having wherein the multiple noncorresponding characteristics are associated with priority levels, and wherein the method further comprises: ranking the multiple noncorresponding characteristics, based on the associated priority levels, to generate ranked noncorresponding characteristics; and providing an indication of the ranked noncorresponding characteristics.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Regarding claim 12, Hu in view of Enthed and Kalaboukis teach the method of claim 8, Hu teaches further comprising: determining whether the noncorresponding value associated with the one or more noncorresponding characteristics satisfies a threshold (as disclosed in Hu, page 1, last par., the system compares to the price, when the expected price does not correspond with the difference plan, wherein, it can be understood that the expected price is noncorresponding characteristic); generating an alert based on the noncorresponding value associated with the one or more noncorresponding characteristics satisfying the threshold (as disclosed in Hu’s Page 1, last par., indicating the transaction is unsuccessful); and providing an indication of the alert (as disclosed in Hu’s Page 1, last par., indicating the transaction is unsuccessful alerting the user).
Regarding claim 13, Hu in view of Enthed and Kalaboukis teach the method of claim 8.
However, Hu in view of Kalaboukis do not explicitly teach further comprising: updating the list of items to generate an updated list of items such that the updated list of items does not include at least a portion of the one or more noncorresponding characteristics; and providing the updated list.
Enthed teaches further comprising: updating the list of items to generate an updated list of items such that the updated list of items does not include at least a portion of the one or more noncorresponding characteristics (Enthed’s Par. [0126] discloses the produces can be given priority levels for potential products for produce arrangement; the produce can be given virtual prices; since the expected values are always given to the produce by the user in Hu’s invention, in the case wherein the expected price is non-compliant [noncorresponding] or compliant, in both cases, the produces are always being identified first before even this compliance determination); and providing the updated list (Pars. [0125-127] discloses the product arrangement is given based on the prioritization).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Enthed of having further comprising: updating the list of items to generate an updated list of items such that the updated list of items does not include at least a portion of the one or more noncorresponding characteristics; and providing the updated list.
Wherein having Hu’s method having further comprising: updating the list of items to generate an updated list of items such that the updated list of items does not include at least a portion of the one or more noncorresponding characteristics; and providing the updated list.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Regarding claim 14, Hu in view of Enthed and Kalaboukis teach the method of claim 8.
However, Hu in view of Kalaboukis does not explicitly teach further comprising: determining a visual characteristic corresponding to an aspect included in at least a portion of the one or more noncorresponding characteristics; and providing, to the augmented reality device, information that identifies the visual characteristic to cause the augmented reality device to display the information that identifies the visual characteristic for display via a user interface of the augmented reality device.
Enthed teaches further comprising: determining a visual characteristic corresponding to an aspect included in at least a portion of the one or more noncorresponding characteristics (Par. [0123] discloses detecting features in the scene and identify the produce based on the detected features Par. [0124]; Par. [0124] discloses the system search in the image repository [elimination of produces not matching the detected features and are not likely to be included in the catalog of furnishings for one instance] to identify the product and its features being compared against a set of rules [aspects being associated with the item]); and providing, to the augmented reality device (Par. [0151] discloses “the price tag applicator includes an augmented lighting engine…is used in augmented reality exampled…operates to present a price tag with virtual lighting”), information that identifies the visual characteristic to cause the augmented reality device to display (Par. [0151] discloses “augmented reality…the augmented lighting engine receives information about the placement of the virtual price including the lighting conditions around where the virtual price tag is attached…instructs the AR viewer to display augmented lighting to the virtual price tag.”) the information that identifies the visual characteristic for display via a user interface of the augmented reality device (Par. [0124] the identification of the produce is being performed based on the detected features in the image and filter the objects against a set of rules; further disclosed in [0126] wherein the detected potential produces are analyzed by comparing the image data of the potential produces with models of sample images of the products based on a prioritization score [degree of similarity] to generate similar produce arrangement for showing the virtual price tag in Par. [0112]; and identify the products based on the processing as discussed according to Pars. [0127-0128] for the virtual reality).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Enthed of having further comprising: determining a visual characteristic corresponding to an aspect included in at least a portion of the one or more noncorresponding characteristics; and providing, to the augmented reality device, information that identifies the visual characteristic to cause the augmented reality device to display the information that identifies the visual characteristic for display via a user interface of the augmented reality device.
Wherein having Hu’s method having further comprising: determining a visual characteristic corresponding to an aspect included in at least a portion of the one or more noncorresponding characteristics; and providing, to the augmented reality device, information that identifies the visual characteristic to cause the augmented reality device to display the information that identifies the visual characteristic for display via a user interface of the augmented reality device.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Regarding claim 15, Hu in view of Enthed and Kalaboukis teach the method of claim 14, Hu teaches further comprising: obtaining user input provided via the user interface of the augmented reality device (Hu, Page 1, Step 1, the user enters input through the interface of the augmented reality device).
However, Hu in view of Kalaboukis do not explicitly teach wherein the user input indicates a confirmation or a nonconfirmation that the visual characteristic corresponds to a visual characteristic associated with one or more features of the plurality of features.
Enthed teaches wherein the user input indicates a confirmation or a nonconfirmation that the visual characteristic corresponds to a visual characteristic associated with one or more features of the plurality of features (The user enters the expected value for the item and determine to purchase the item or not based on rationality based on the output of the system; and the user scan the produce with the virtual reality device hence indicating confirming the product visually based on its characteristics such as the features of the product in the image according to Par. [0151] discloses “augmented reality…the augmented lighting engine receives information about the placement of the virtual price including the lighting conditions around where the virtual price tag is attached…instructs the AR viewer to display augmented lighting to the virtual price tag.”).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Enthed of having wherein the user input indicates a confirmation or a nonconfirmation that the visual characteristic corresponds to a visual characteristic associated with one or more features of the plurality of features.
Wherein having Hu’s method having wherein the user input indicates a confirmation or a nonconfirmation that the visual characteristic corresponds to a visual characteristic associated with one or more features of the plurality of features.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Regarding claim 16, Hu in view of Enthed and Kalaboukis teach the method of claim 8.
However, Hu in view of Kalaboukis do not explicitly teach wherein the object is associated with an initial value; and the method further comprises: obtaining location information that identifies a location of the augmented reality device; and adjusting the initial value based on obtaining the location information that identifies the location of the augmented reality device.
Enthed teaches wherein the object is associated with an initial value; and the method further comprises: obtaining location information that identifies a location of the augmented reality device (Par. [0167] discloses obtaining the location of the identified object based on using the augmented reality device); and adjusting the initial value based on obtaining the location information that identifies the location of the augmented reality device (the product being given a virtual tag such as disclosed in Par. [0166]; Par. [0167] discloses the virtual price tag can be changed or updated [adjusted as claimed]).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to: obtain item-specific data that indicates an expected value associated with an item in a list of items, with the teachings of Enthed of having wherein the object is associated with an initial value; and the method further comprises: obtaining location information that identifies a location of the augmented reality device; and adjusting the initial value based on obtaining the location information that identifies the location of the augmented reality device
Wherein having Hu’s method having wherein the object is associated with an initial value; and the method further comprises: obtaining location information that identifies a location of the augmented reality device; and adjusting the initial value based on obtaining the location information that identifies the location of the augmented reality device
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting. Since both Hu and Enthed both perform virtual reality price tag processing for items. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Enthed’s system improves augmented reality system by in having improved visibility of price tag through effective price tag locating and augmenting, (see Enthed’s Par. [0116]).
Claims 10 is rejected under 35 U.S.C. 103 as being unpatentable over Chen Hu (Foreign Patent Document “CN 112884545 A” hereinafter as “Hu”) in view of Martin Enthed et. al. (“US 2023/0298050 A1” hereinafter as “Enthed”) further in view of Chris Kalaboukis (“US 11,195,214 B1” hereinafter as “Kalaboukis”) and Kai Li Lim et. al. (“Review: A Unified Telemetry Platform for Electric Vehicles and Charging Infrastructure, Jan. 2020, Connected Vehicles in the Internet of Things, pp. 167-219” hereinafter as “Lim”).
Regarding claim 10, Hu in view of Enthed and Kalaboukis teach the method of claim 8.
However, Hu in view of Enthed and Kalaboukis does not explicitly teach further comprising: determining an itemized value for at least one noncorresponding characteristic of the one or more noncorresponding characteristics; and providing an indication of the itemized value for the at least one noncorresponding characteristic.
Lim teaches further comprising: determining an itemized value for at least one noncorresponding characteristic of the one or more noncorresponding characteristics (the information of the items identified through the augmented reality such as all of these processing mapped to Hu and Anthed, being billed as itemized billing as taught in Lim’s Abstract and Section 8.7, 1st 2 Pars.); and providing an indication of the itemized value for the at least one noncorresponding characteristic (then the indication of the noncorresponding characteristic would be displayed in itemized value according to Lim’s Abstract and Section 8.7, 1st 2 Pars.).
Therefore, it would have been obvious to one or ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teaches of Hu in view of Enthed and Kalaboukis of having a method for verifying item-specific data based on data captured by an augmented reality device, the system comprising: one or more memories; and one or more processors, communicatively coupled to the one or more memories, with the teachings of Lim of having further comprising: determining an itemized value for at least one noncorresponding characteristic of the one or more noncorresponding characteristics; and providing an indication of the itemized value for the at least one noncorresponding characteristic.
Wherein having Hu’s method of having further comprising: determining an itemized value for at least one noncorresponding characteristic of the one or more noncorresponding characteristics; and providing an indication of the itemized value for the at least one noncorresponding characteristic.
The motivation behind the modification would have been to improve commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, and further to improve data generation and collection through smartphone application for living monitoring and producing itemized billing for user’s efficiency of using a system. Since both Hu and Lom both perform product identification for website services. Wherein Hu’s system improves commodity exhibition and sale model through image recognition and analysis to promote consumer focus and making efficient judgement, see (Hu’s Page 1, Background technique and summary of invention’s 1st Par.), and Lim’s system improves data generation and collection through smartphone application for living monitoring and producing itemized billing for user’s efficiency of using a system, (see Lim’s Abstract).
Pertinent Prior Art(s)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Guheen; Michael F. et. al., “US 20040107125 A1”, discloses a system, method, and article of manufacture are provided for planning the testing of components of an existing network framework. First, a pictorial representation of an existing network framework is displayed along with a plurality of components of the existing network framework. Thereafter, the components of the existing network framework are indicia coded in order to convey a plan by which the components of the existing network framework are to be tested. The components may be indicia coded in order to convey an order of the testing or which components of the existing network framework are to be tested.
Stankiewicz; Brian J. et. al., “US 20100086278 A1”, discloses systems and methods for optimizing properties of objects within a scene or achieve a visual goal.
JAKKA; Anoop et. al., “US 20210279852 A1”, discloses a method for using a virtual representation of an indoor environment to identify contents that have been damaged (e.g., by flooding). A virtual representation of a physical scene of an indoor environment is processed to identify a list of contents in the physical scene. The virtual representation may include 2-dimensional representations of the physical scene (e.g., images or video) or a 3-dimensional representation of the physical scene (e.g., 3D digital model). A reference line is determined in the virtual representation that is indicative of a maximum vertical extent of the damage in the physical scene. The position of the reference line is compared with the position of the identified contents in the virtual representation to determine contents that are likely to be damaged. For example, the contents that are at or below a plane represented by the reference line in the virtual representation may be identified as damaged.
Foster; Gary et. al., “US 11803781 B2”, discloses systems and methods of the present disclosure use one or more processor(s) to receive a consumable preference and a daily score intake value associated with a user and to obtain a content data regarding consumable item including an amount of a first nutrient found in the consumable item. The processor(s) utilizes, in real-time, a nutrient prediction machine learning model to ingest the content data regarding the consumable item and predict an amount of a second nutrient in the consumable item based on the content data and a decision tree library of thousand nutrient decision trees. The processor(s) determines zero-scored consumable item based on the daily score intake value, the amount of the first nutrient, the amount of the second nutrient, and the consumable preference. The processor(s) instructs a computing device to utilize a graphical user interface element to identify the zero-scored consumable item on a screen of the computing device.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/PHUONG HAU CAI/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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