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 .
Claims 1-3, 5-11, and 13-19 are pending.
Claims 1-3, 5, 6, 9, 16-20, and 13-19 are amended.
Claim 15 is cancelled. Claim 4, 12, and 20 were previously cancelled.
Response to Arguments
Applicant's arguments and amendments filed with respect the objection to the title have been fully considered and are persuasive. The objection to the title has been withdrawn.
Applicant's arguments and amendments filed with respect the objection to the claim 9 have been fully considered and are persuasive. The objection to the claim has been withdrawn.
Applicant's arguments with regards to Section 101 for being directed to an abstract idea have been fully considered but they are not persuasive. Applicant argues that that the human mind is not equipped to perform the limitations of the claimed invention, but fails to identify any reasoning why the human mind cannot perform those limitations. The division of an image into sections is a well known human process, including the processing of a passport or ID. For example, a customs agent may be trained to look at a photo section, passport number section, date sections, hologram sections, and the like. Many other versions of visual comparison operations are well known to be human mental games. See, for example, Spot the Difference or Photo Hunt games, or in many police comparison practices such as comparing fingerprints or identifying suspects in police lineups (https://en.wikipedia.org/wiki/Visual_comparison).
As noted in a case cited by Applicant’s arguments, the Federal Circuit held that a method of playing a dice game which included the steps of placing a wager, rolling the dice, and paying a payout amount was an abstract idea—namely, a method of organizing human activity—and that merely applying the steps on a computer fell short of reciting an inventive concept sufficient to transform the abstract idea into a patent-eligible application. In re Marco Guldenaar Holding B.V., 911 F.3d 1157, 1160-61. Similarly, in this case, the human process of visually inspecting products for authentication is not transform the abstract idea by using a computer to communicate for additional images or information. Such processes are not “necessarily rooted in computer technology”, but rather use technology as the environment to perform the abstract idea such that is may be performed at multiple locations as easily as it has been done in person, similar to the authentication of bank notes or identification documents based on known images different identifiers in different sections. Thus, the problem being addressed is not technical in nature, but a business problem of addressing the reliability of products shipped. Nor is there a technical problem, but rather the arguments describe a business problem of information gathering and requests for additional information based on previously received data. That is, the arguments at best point a sales problem that occurs in all human sales transactions. As such, the arguments are not persuasive.
Applicant’s arguments with respect to Section 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Interpretation and Objections
Claims 1 and 17-19 recite determining a first feature of a first target frame, among a first plurality of features; determining a second feature of a second target frame, among a second plurality of features, wherein the first feature has highest distinguishability among the first plurality of features, the second feature has highest distinguishability among the second plurality of features”. It is noted that the “feature has highest distinguishability” is a limitation of an object to be photographed, not of the system or method. As such, these features amount to non-functional descriptive language limit the function of the claims in any way.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-3, 5-11, 13, 14, 16-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 17-19 recite “the first feature has highest distinguishability among the first plurality of features, the second feature has highest distinguishability among the second plurality of features”. The term “highest distinguishability” in claims 1 and 17-19 is a relative term which renders the claim indefinite. The term “highest” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is noted that the specification does discuss the characteristic portion of the product refers to, for example, a portion having higher distinguishability in identification of the product than other portions in paragraph [0066]. However, while the specifications discuss portions of an object relative to other, it is unclear how a distinguishability would be determined between a bar code v. custom hardware, or a serial number location v. trademark name. As such, it is unclear what the claimed apparatus is doing to define and determine that a “feature has highest distinguishability” among the first plurality of features. As such, the scope of the claims is unclear. Appropriate correction is required.
Dependent claims 2-3, 5-11, 13, 14, and 16 are rejected at least for incorporating the objected to subject matter of the claims from which they depend.
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 1-3, 5-11, 13, 14, 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Representative claim 17 recites “receiving, …, a first image associated with a first product, and a second image associated with a second product; dividing, …, the first image into a first plurality of sections, and the second image into a second plurality of sections; determining, …, a first feature of a first target frame, among a first plurality of features; determining, …, a second feature of a second target frame, among a second plurality of features, wherein the first feature has highest distinguishability among the first plurality of features, the second feature has highest distinguishability among the second plurality of features, the first target frame corresponds to a first section of the first plurality of sections, the second target frame corresponds to a second section of the second plurality of sections, and the second plurality of features corresponds to the second plurality of sections; generating, …, based on the determination of the first feature, a prompt for a third image corresponding to the first target frame, wherein the third image has a higher resolution than the first image; extracting, …, a third target frame from the third image, wherein the third target frame corresponds to the first product; identifying, …, that the first product matches the second product, based on the second target frame and the third target frame; …; generating, …, a prompt for an input of product information related to the second product, wherein the generation of the prompt is based on the identification that the first product matches the second product, the product information is related to conditions of the second product; and ….”. Therefore, the claim as a whole is directed to “Product Authentication Processes”, which is an abstract idea because it is a method of organizing human activity, including fundamental economic principles or practices such as mitigating risk, and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions), and mental processes, including concepts performed in the human mind (including an observation, evaluation, judgment, opinion). “Product Authentication Processes” is considered to be is a method of organizing human activity and mental process because the judgments made about authenticity may be made mentally based on human observations. Humans have regularly used human observations and authentication processes, including match photographs of goods or document products to known images available for review of stored in their heads. As such, the claims are directed to an abstract idea.
Claims 1, 18, and 19 recite substantially similar features to those recited in representative claim 17 and are directed to an abstract idea for substantially the same reasons.
This judicial exception is not integrated into a practical application. In particular, claim 1 recites a display device and CPU, and control the display device to output a result of the identification indicating that the first product matches the second products; and output the generated prompt for the input of the first product information, claim 17 recites a computer, 18 recites a non-transitory computer readable medium storing instructions that may be executed by a computer, and claim 19 recites a device associated with a first user, a device associated with a second user, and an information processing apparatus. These additional elements individually or in combination do not integrate the exception into a practical application. That is, the recitations of additional elements amount merely reciting the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). In fact, it is clear from the specification that only generic computing elements such a CPU, MPU, ASIC or FPGA are provided as the basis for technology for implementing the abstract idea. See paragraph [0035] of the instant specification. The use of generic computer components to perform their intended function does not address a technical problem or provide a technological solution. Such generically recited additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claims 1 and 17-19 are directed to an abstract idea.
Claims 1 and 17-19 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to integration of the abstract idea into a practical application, the additional elements of any of the independent claims, individually and in combination, are merely being used to apply the abstract idea to a technological environment. As noted above, the specification recites only generic computing elements as the environment for performing the abstract idea. Accordingly, claims 1 and 17-19 are ineligible.
Dependent claims 2, 3, 5-11, 13-16 merely further limit the abstract idea and are thereby considered to be ineligible.
Dependent claim 2 further limits the abstract idea of Product Authentication Processes” by introducing the element of identifying whether the first product matches the second product based on the first feature extracted for each resolution of a plurality of resolutions of a captured image of the second product and based on the second feature extracted for each resolution of a plurality of resolutions of a captured image of the first product, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 2 is also non-statutory subject matter.
Dependent claim 3 further limits the abstract idea of Product Authentication Processes” by introducing the element of identify that the first product matches the second product based on a feature of each section of the first plurality of sections, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 3 is also non-statutory subject matter.
Dependent claim 5 further limits the abstract idea of Product Authentication Processes” by introducing the element of determine the first feature of the first target frame of the first image included in a first product video associated with the first product ;determine the second feature of the second target frame of the second image included in a second product video associated with the second product; identifying that the first product matches the second product based on: a product feature extracted from an image included in a first product video associated with the first product, and a product feature extracted from an image included in a second product video associated with the received second product, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 5 is also non-statutory subject matter.
Dependent claim 6 further limits the abstract idea of Product Authentication Processes” by introducing the element of acquiring product feature of the first product from a device of a first user, acquire a product feature of the second product from a device of a second user; collate the product feature of the first product with the product feature of the second product, and identify the received first product matches the second authentic product based on the collation of the product feature of the first product with the product feature of the second product, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 6 is also non-statutory subject matter.
Dependent claim 7 further limits the abstract idea of Product Authentication Processes” by introducing the element of storing first personal authentication information of a first user associated with the first product, acquire second personal authentication information of the first user from a device of the first user; collate the first personal authentication information of the first user with the second personal authentication information of the first user; and execute personal authentication of the first user based on the collation of the first personal authentication information of the first user with the second personal authentication information of the first user, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 7 is also non-statutory subject matter.
Dependent claim 8 further limits the abstract idea of Product Authentication Processes” by introducing the element of execute personal authentication of a first user associated with the first product, based on personal authentication information, and the personal authentication information of the first user includes at least one of fingerprint information of the first user, iris information of the first user, or face information of the seller first user, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 8 is also non-statutory subject matter.
Dependent claim 9 further limits the abstract idea of Product Authentication Processes” by introducing the element of storing first personal authentication information of a second user, wherein the second user is a purchaser of the second product, and acquiring second personal authentication information of the second user from a device of the second user; collate the first personal authentication information of the second user with the second personal authentication information of the second user; and execute personal authentication of the second user based on the collation of the first personal authentication information of the second user with the second personal authentication information of the second user, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 9 is also non-statutory subject matter.
Dependent claim 10 further limits the abstract idea of Product Authentication Processes” by introducing the element of execute personal authentication of a second user based on personal authentication information of the second user, and the personal authentication information of the second user includes at least one of fingerprint information of the second user, iris information of the second user, or face information of the second user, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 10 is also non-statutory subject matter.
Dependent claim 11 further limits the abstract idea of Product Authentication Processes” by introducing the element of guiding a first user associated with the first product to capture an image of the first target frame, and output, to a device of the first user, information that prompts the capture of the image of the first target frame, or guide a second user to capture an image of the second target frame; and output, to a device of the second user, information that prompts the capture of the image of the second target frame, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 11 is also non-statutory subject matter.
Dependent claim 13 further limits the abstract idea of Product Authentication Processes” by introducing the element of product identification information of the second product, personal authentication information of a first user associated with the first product, personal authentication information of a second user associated with the second product, product information of the second product, and product trade information indicating a transaction state of the second product, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 13 is also non-statutory subject matter.
Dependent claim 14 further limits the abstract idea of Product Authentication Processes” by introducing the element of storing product identification information of the second product, the personal authentication information of the first user, the product information of the second product, and the product trade information of the second product, based on a blockchain technology, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 14 is also non-statutory subject matter.
Dependent claim 15 further limits the abstract idea of Product Authentication Processes” by introducing the element of operation to prompt a second user to input first product information related to the second product, wherein the execution of the operation is based on the identification that the first product matches the second product; and output, to the second user, information to prompt for an input of second product information, wherein the second product information is related to the second product, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 15 is also non-statutory subject matter.
Dependent claim 16 further limits the abstract idea of Product Authentication Processes” by introducing the element of acquiring the second product information from a device of the second user; and updating third product information related to the blank item related to a same type as the second product with the second product information, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 16 is also non-statutory subject matter.
Dependent claims 2, 3, 5-11, 13-16 also do not integrate the abstract idea into a practical application. The dependent claims 7, 9, and 13 recite a memory, and claim 14 further recites using blockchain technology. These additional elements merely generally link the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(I) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide significantly more. That is, the claims provide no practical limits or improvements to any technology. Accordingly, dependent claims 2, 3, 5-11, 13-16 are also ineligible.
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.
Claims 1-3, 5-10, 12-14, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20190228174 to Withrow et al. in view of U.S. Patent Application Publication No. 20210081698 to Lindeman et al.
With regards to claims 1, 17, 18, and 19, Withrow et al. teaches:
a device associated with a first user; a device associated with a second user (paragraph [0078])
performs a central processing unit (CPU) (paragraph [0132]) configured to:
receiving, by a computer, a first image associated with a first product, and a second image associated with a second product (paragraph [0046], “To the limitations of the available computational resources, each and every digital fingerprint identifying a determined portion of a physical object is different from each and every other digital fingerprint identifying a different physical object or identifying a different portion of the same physical object. And to the limitations of the available computational resources and the preservation of the determined portion of the physical object on which a first digital fingerprint is generated, each and every subsequent digital fingerprint identifying the same determined portion of the same physical object is statistically the same as the first digital fingerprint.”) or captured product video (paragraph [0054], “mages may, for example, be two dimensional (2-D), three dimensional (3-D), or in the form of video. Thus a scan may refer to one or more images or digital data that defines such an image or images captured by a scanner, a camera, an imager, a 3D-sense device, a LiDAR-based device, a laser-based device, a specially adapted sensor or sensor array (e.g., a CCD array), a microscope, a smartphone camera, a video camera, an x-ray machine, a sonar, an ultrasound machine, a microphone (i.e., any instrument for converting sound waves into electrical energy variations), and the like.”; paragraph [0124], “In some embodiments, the digital companion may be used for security challenges for users or third parties during authentication. In order to prevent the submission of fraud data, the authentication system may ask a user or other party wanting to perform authentication to submit images or video from different orientations to further establish credibility of possession.”);
dividing, by the computer, the first image into a first plurality of sections, and the second image into a second plurality of sections (paragraph [0046], “And to the limitations of the available computational resources and the preservation of the determined portion of the physical object on which a first digital fingerprint is generated, each and every subsequent digital fingerprint identifying the same determined portion of the same physical object is statistically the same as the first digital fingerprint. In at least some cases, a digital fingerprint, as the term is used herein, is generated in a method that includes acquiring a digital image, finding points of interest within that digital image (e.g., generally, regions of disparity where “something” is happening, such as a white dot on a black background or the inverse), and characterizing those points of interest into one or more feature vectors extracted from the digital image. Characterizing the points of interest may include assigning image values, assigning or otherwise determining a plurality of gradients across the image region, or performing some other technique. The extracted feature vectors may or may not be analyzed or further processed. Instead, or in addition, the extracted feature vectors that characterize the points of interest in a region are aggregated, alone or with other information (e.g., with location information) to form a digital fingerprint.”);
determining, by the computer, a first feature of a first target frame, among a first plurality of features (paragraph [0046], “Characterizing the points of interest may include assigning image values, assigning or otherwise determining a plurality of gradients across the image region, or performing some other technique. The extracted feature vectors may or may not be analyzed or further processed. Instead, or in addition, the extracted feature vectors that characterize the points of interest in a region are aggregated, alone or with other information (e.g., with location information) to form a digital fingerprint.”);
determining, by the computer, a second feature of a second target frame, among a second plurality of features, wherein the first feature has highest distinguishability among the first plurality of features, the second feature has highest distinguishability among the second plurality of features, the first target frame corresponds to a first section of the first plurality of sections, the second target frame corresponds to a second section of the second plurality of sections, and the second plurality of features corresponds to the second plurality of sections (paragraph [0086], “FIG. 3 is a simplified flow diagram of an example process to implement a secure digital fingerprint key object database. In this process, the method comprises the following acts: provisioning a data store operatively coupled to the computing system for storing and accessing digital records, block 1502; initializing a key object record in the data store to store data associated with a physical key object, block 1504; storing a digital fingerprint of the key object in the key object record, block 1506; creating a digital record in the data store, block 1508; linking the digital record to the digital fingerprint of the key object to securely control access to the digital record, block 1510; receiving a tendered access key via a programmatic interface or user interface coupled to the computing system, block 1512; querying the data store based on the tendered access key to identify a matching digital fingerprint of a key object, block 1514; and in a case that the querying step identifies a matching digital fingerprint of a key object within a prescribed level of confidence (e.g., 75% confidence, 95% confidence, 99.999% confidence, or some other level of confidence), granting access to the linked digital record secured by the matching key object, block 1516.”);
generating, by the computer, based on the determination of the first feature, … a third image corresponding to the first target frame, wherein the third image has a higher resolution than the first image (paragraph [0126], “Consider, as an example, an automated drone authenticating objects within a scene. The sensors on the drone can collect more data on objects that are in closer proximity. As the drone moves closer to other objects, it obtains higher resolution images, and the original, lower-scored digital fingerprint may be supplanted for higher-scored versions of those particular objects.”; paragraph [0131], “The same process, or processes along these lines, may be applied at re-identification. In these cases, the imager approaches an object while extracting progressively better (i.e., more information-filled) digital fingerprints until the system either successfully re-identifies the object or determines the object is not in its database. The system then reports the results as desired. Either the determined best induction, or some set of inductions, is preserved for later us”);
extracting, by the computer, a third target frame from the third image, wherein the third target frame corresponds to the first product (paragraph [0127], “Each authentication zone may have its own expectation about the quality of data that may be obtained through collection of digital fingerprints. In this approach, objects within the determined highest qualified view of sensors may be scored as anchor authentications. Each subsequent zone may be indexed in parallel by collecting digital fingerprints that may be scored appropriately to the quality of sensor data collected at that time. As sensors are moved through a scene, objects may be re-authenticated. Each object's digital fingerprint may be flagged as an anchor within the digital pedigree when higher-quality data is collected by a sensor.”);
identifying, by the computer, that the first product matches the second product, based on the second target frame and the third target frame (paragraph [0018], “storing a digital fingerprint of the physical key object in the key object record; creating a digital record in the data store that is not the key object record; linking the digital record to the digital fingerprint of the key object to securely control access to the linked digital record; receiving a tendered access key via a programmatic or user interface coupled to the computing system; querying the data store based on the tendered access key to identify a matching digital fingerprint of a key object; and in a case that the querying step identifies a matching digital fingerprint of a key object within a prescribed level of confidence, granting access to the linked digital record secured by the matching key object.”);
controlling, by the computer, …. to output a result of the identification indicating that the first product matches the second product (paragraph [0131], “In these cases, the imager approaches an object while extracting progressively better (i.e., more information-filled) digital fingerprints until the system either successfully re-identifies the object or determines the object is not in its database. The system then reports the results as desired.”);
generating, by the computer, a prompt for an input of product information related to the second product, wherein the generation of the prompt is based on the identification that the first product matches the second product, the product information is related to conditions of the second product (paragraph [0038], “Data associated with the digital pedigree may be referred to as digital pedigree data. Various digital pedigree data, as described in the present disclosure, includes data associated with a particular physical object, context data, supplemental context data (e.g., location data, metadata, media such as audio and video, scientific data, sensor data, records of purchase, records of transfer of the associated physical object, certification data, authentication data, and many other types of data. The pedigree data may be added to, subtracted from, modified, or acted on in other ways at various times.”; paragraph [0042], “After the rights to access the protected digital record have been transferred or shared by a possessor of the original key object or its digital fingerprint, the other objects now become key objects. …. Gaining access may include providing the ability to read, execute, unlock, modify, supplement, delete, or otherwise control the digital record”; paragraph [0059], “In an embodiment, each transaction related to a pedigreed object updates a data store showing ownership or other relationships to the object. When the possessor has or is ready to engage in a transaction that concerns or relates to the object, such as insuring, renting, or sale of the object, the possessor may send information, for example a link such as a secure URL, to a digital fingerprint pedigree and/or digital companion data store containing the record and/or curated records related to the object.”); and
outputting, by the computer, the generated prompt for the input of the product information (paragraph [0090], “In one embodiment, the taught approach provides the ability, in association with a transaction, to enable selected users to review and incorporate data from online pedigrees related to the transaction. For example, in an online marketplace transaction, the goods being exchanged, the individuals or entities involved in the transaction, and even the finance and escrow services may all have existing pedigrees that can be accessed by parties to the transaction for the purpose of, for example, determining their suitability.”), but fails to explicitly teach a display device or a prompt for a higher resolution image. However, Lindeman et al. teaches
generating, by the computer, based on the determination of the first feature, a prompt for a third image corresponding to the first target frame, wherein the third image has a higher resolution than the first image (paragraph [0051], “The results of the analysis include Subject parts detection (produced by the module 132), damage levels (produced by the modules 134 and 136 of FIG. 1A), repair costs (produced by the module 144), identification and accuracy confidence levels and visual bounding boxes for parts and damage area highlights (as performed by the module 146). In some embodiments, the engine 130 may also be configured to control the data acquisition devices. For example, if a computed confidence level for a derived output is below some reference threshold value, the engine 130 may send a request to one of the data acquisition devices (e.g., one or more of the cameras 110 a-n) to obtain another data capture (another image) at a higher resolution or zoom, or from a different view or perspective. Multiple processes are thus implemented to work in concert to generate results. Specific processes are developed to solve each of the feature identification requirements. An assembly of the features described herein may be termed the awareness context.”);
extracting, by the computer, a third target frame from the third image, wherein the third target frame corresponds to the first product (paragraph [0071], “Additionally or alternatively, the field recognition engine may employ a template matching technique to identify feature matches between the received image and document templates. Specifically, template matching can be used to identify regions of the received image that match data field labels and their neighboring regions in one or more document templates. By way of example, in some embodiments, the received image may be compared to one or more document templates, in order to identify matches of data fields. A data field in the received image of the document may be identified by detecting a match with a data field in one of the templates based on, for example, dimensions/shape of the data field, text or graphics label associated with the data field, and/or relative location of the data field on the imaged document.”);
identifying, by the computer, that the first product matches the second product, based on the second target frame and the third target frame (paragraph [0054], “The collection of features can define a fingerprint for the physical object to be analyzed. Thus, an early capture of physical object data (using light-capture devices and/or other sensors to capture/measure data relevant to the structure of the physical object) can establish a baseline of data for a particular object. A subsequent re-run of data capture for the physical object can then facilitate a comparative analysis of structure attributes determined from the re-run of the data capture process relative to structural attributes derived from the baseline data. Alternatively, as noted, when no baseline data exists for the particular object, determination of possible deviation of the physical structure of the object from a normal (or optimal) state may be derived using, among other things, trained learning engines and/or other types of classifiers or processes to determine structural attributes of the physical object. The comparative analysis is used for object identification and determination of structural changes (e.g., prior damage versus new damage, with such comparisons being used for fraud detection).”);
controlling, by the computer, a display device to output a result of the identification indicating that the first product matches the second product (paragraph [0036], “In some implementations, generating the first display data may include generating display data that includes a graphical representation of product comparison data for the first and second products.”; paragraph [0075], “In response to determining that there is a deficiency in the recognized text, the computing system may generate display data for prompting a user of the client device to provide information relating to the missing one or more data fields. For example, the display data may be a graphical user interface including a fillable input form containing the at least one data field. Alternatively, the display data may be a graphical user interface including an application form having the missing data fields highlighted. The computing system may then transmit the display data to the client device in order to solicit additional information from the user(s) associated with the client device.”);
This part of Lindeman et al. is applicable to the system of Withrow et al. as they both share characteristics and capabilities, namely, they are directed to product identification processes. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Withrow et al. to include the information prompting processes as taught by Lindeman et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Withrow et al. in order to improve capability to identify and capture additional data (e.g., video, audio, etc.) for the object being analyzed (see paragraph [0070] of Lindeman et al.).
With regards to claim 2, Withrow et al. teaches: determine the first feature of the first target frame for each resolution of a plurality of resolutions of the first image; determine the second feature of the second target frame for each resolution of a plurality of resolutions of the second image; and identify that the first product matches the second product based on: the determined first feature of the first target frame each resolution of the plurality of resolutions of the first image, and the determined second feature of the second target frame for each resolution of the plurality of resolutions of the second image (paragraph [0125], “In some embodiments, a method of progressive induction, authentication, and identification of objects, which at least in this case may be collectively referred to as “authentication,” is realized where the digital pedigree of a physical object is updated with higher-relevancy data as such data is obtained. In this way, the authentication may be progressively improved.”; paragraph [0126], “As the drone moves closer to other objects, it obtains higher resolution images, and the original, lower-scored digital fingerprint may be supplanted for higher-scored versions of those particular objects.”).
With regards to claim 3, Withrow et al. teaches:
wherein the CPU is further configured to identify that the first product matches the second product, based on a feature of each section of the first plurality of sections and a feature of each section of the second plurality of sections (paragraph [0046], “In at least some cases, a digital fingerprint, as the term is used herein, is generated in a method that includes acquiring a digital image, finding points of interest within that digital image (e.g., generally, regions of disparity where “something” is happening, such as a white dot on a black background or the inverse), and characterizing those points of interest into one or more feature vectors extracted from the digital image. Characterizing the points of interest may include assigning image values, assigning or otherwise determining a plurality of gradients across the image region, or performing some other technique. The extracted feature vectors may or may not be analyzed or further processed. Instead, or in addition, the extracted feature vectors that characterize the points of interest in a region are aggregated, alone or with other information (e.g., with location information) to form a digital fingerprint.”; paragraph [0048], “In the case of a 2-D object, the points of interest are preferably on a surface of the corresponding object; in the 3-D case, the points of interest may be on the surface or in the interior of the object. In some applications, an object “feature template” may be used to define locations or regions of interest for a class of objects. The digital fingerprints may be derived or generated from digital data of the object which may be, for example, image data.”).
With regards to claim 5, Withrow et al. teaches: determine the first feature of the first target frame of the first image included in a first product video associated with the first product; determine the second feature of the second target frame of the second image included in a second product video associated with the second product; and identify that the first product matches the second product based on: the first feature of the first target frame of the first image included in the first product video associated with the first product, and the second feature of the second target frame of the second image included in the second product video associated with the second product (paragraph [0046], “Characterizing the points of interest may include assigning image values, assigning or otherwise determining a plurality of gradients across the image region, or performing some other technique. The extracted feature vectors may or may not be analyzed or further processed. Instead, or in addition, the extracted feature vectors that characterize the points of interest in a region are aggregated, alone or with other information (e.g., with location information) to form a digital fingerprint.”) included in a product video obtained by imaging the authentic product and based on a product feature extracted from an image included in a product video obtained by imaging the received product (paragraph [0038], “Various digital pedigree data, as described in the present disclosure, includes data associated with a particular physical object, context data, supplemental context data (e.g., location data, metadata, media such as audio and video, scientific data, sensor data, records of purchase, records of transfer of the associated physical object, certification data, authentication data, and many other types of data.”; paragraph [0054], “Images may, for example, be two dimensional (2-D), three dimensional (3-D), or in the form of video.”).
With regards to claim 6, Withrow et al. teaches: acquiring the first feature of the first product from a device of a first user (paragraph [0051], “In an embodiment, features may be used to represent information derived from a digital image in a machine-readable and useful way. Features may comprise point, line, edges, blob of an image, etc. There are areas such as image registration, object tracking, and object retrieval etc. that require a system or processor to detect and match correct features.”), acquire the second feature of the second product from a device of a second user (paragraph [0027], “initializing a second key object record in the data store to store data associated with the second key object; storing a digital fingerprint of the second key object in the second key object record; and further linking the digital record to the digital fingerprint of the second key object to enable access to the digital record without requiring the first key object. The first key object may permit first access rights to the digital record and the second key object may permit second access rights to the digital record, where the second access rights are different from the first access rights. The linked digital record may include sensitive data so that the sensitive data is protected by requiring that a token comprising a digital fingerprint of the first or second key object be presented to access the sensitive data.”); collate the first feature of the first product with the second feature of the second product, and identify the received first product matches the second authentic product based on the collation of the product feature of the first product with the product feature of the second product (paragraph [0041], “The computing system checks that the digital fingerprint properly matches the record for the key object in the digital record. If such a match is established, the computing system grants access to the digital record or digital object secured by the key object, circumscribed by, or otherwise in accordance, with permissions specified by the key object record.”).
With regards to claim 7, Withrow et al. teaches: a memory configured to store first personal authentication information of a first user associated with the first product (paragraph [0133]), wherein the CPU is further configured to acquire second personal authentication information of a first user associated with the first product, acquire second personal authentication information of the first user from a device of the first user (paragraph [0023], “The method may further include receiving an access key via a third-party app or user interface; authenticating the access key based on identifying a matching key object record in the data store; and conditioned on the authenticated key granting rights to change access rights, changing the access rights to the corresponding digital record to enable use of credentials comprising at least one of a specified user name, a specified password, and a second key object defined by a digital fingerprint of the second key object.”; paragraph [0024], “The method may further include receiving an access key via a third-party app or user interface; authenticating the access key based on identifying a matching key object record in the data store;”);
collate the first personal authentication information of the first user with the second personal authentication information of the first user (paragraph [0087], “Digital pedigree and contextual data about each transaction or pedigree may be used by many parties, such as appraisers, distributors, resellers, and merchants. Data included as part of a pedigree may be pre-packaged or pre-authorized for use by the possessor of the object.”); and
execute personal authentication of the first user based on the collation of the first personal authentication information of the first user with the second personal authentication information of the first user (paragraph [0018], “receiving a tendered access key via a programmatic or user interface coupled to the computing system; querying the data store based on the tendered access key to identify a matching digital fingerprint of a key object; and in a case that the querying step identifies a matching digital fingerprint of a key object within a prescribed level of confidence, granting access to the linked digital record secured by the matching key object.”).
With regards to claim 8, Withrow et al. teaches the execute personal authentication of a first user associated with the first product, based on personal authentication information, and the personal authentication information of the first user includes at least one of fingerprint information of the first user, iris information of the first user, or face information of the seller first user (paragraph [0018], “receiving a tendered access key via a programmatic or user interface coupled to the computing system; querying the data store based on the tendered access key to identify a matching digital fingerprint of a key object; and in a case that the querying step identifies a matching digital fingerprint of a key object within a prescribed level of confidence, granting access to the linked digital record secured by the matching key object.”).
With regards to claim 9, Withrow et al. teaches:
storing first personal authentication information of a second user, wherein the second user is a purchaser of the second product, and acquiring second personal authentication information of the second user from a device of the second user (paragraph [0024], “The method may further include receiving an access key via a third-party app or user interface; authenticating the access key based on identifying a matching key object record in the data store;”), and
collate the first personal authentication information of the second user with the second personal authentication information of the second user; and execute personal authentication of the second user based on the collation of the first personal authentication information of the second user with the second personal authentication information of the second user (paragraph [0027], “The computer-implemented method may further include receiving an access key tendered via a programmatic or user interface; authenticating a user as a proprietor of the digital record secured by the first key object based on the access key;”).
With regards to claim 10, Withrow et al. teaches: execute personal authentication of a second user based on personal authentication information of the second user, and the personal authentication information of the second user includes at least one of fingerprint information of the second user, iris information of the second user, or face information of the second user (paragraph [0118], “In one embodiment, digital companions and their related pedigrees may be used as a store for any biometric data for an individual or object. Consider examples, where specific data is collected related to an individual or object:”; paragraph [0119], “Unique behavior, such as gait or keystroke habit”; paragraph [0120], “Specific audio such as voice patterns”; paragraph [0121], “Digital fingerprints of an iris”; paragraph [0122], “Digital fingerprints of fingerprints”; paragraph [0123], “Thermal signature”).
With regards to claim 13, Withrow et al. teaches:
product identification information of the second product, personal authentication information of a first user associated with the first product, personal authentication information of a second user associated with the second product, product information of the second product, and product trade information indicating a transaction state of the second product (paragraph [0047], “The digital fingerprints are typically stored in a repository such as a register, a physical memory, an array, a database, data store, or some other repository. Storing the digital fingerprint in the repository may include or in some cases be referred to as inducting the respective physical object into the repository.”; paragraph [0083], “A sample record may correspond to one digital pedigreed object. The record may be maintained, for example, in a data store 1314 as shown in FIG. 2. The record may have fields including a record number, first pointers, an identifier of the object, security information, and second pointers. The first pointers may include for example, pointers to digital fingerprints of the pedigreed object, other identifiers, or models of the object, and other pedigree and transaction history data. Other fields in the record may comprise or point to one or more of a chain of possession table, a chain of title table, legal terms and conditions, or the like.”; paragraph [0094], “As a further elaboration of the embodiment, the information relevant to the transaction may be incorporated with distributed ledger technologies (e.g., blockchain) and/or cryptography-based currencies.”).
With regards to claim 14, Withrow et al. teaches: to store the product identification information of the second product, the personal authentication information of the first user, the product information of the second product, and the product trade information of the second product, based on a blockchain technology (paragraph [0094], “As a further elaboration of the embodiment, the information relevant to the transaction may be incorporated with distributed ledger technologies (e.g., blockchain) and/or cryptography-based currencies.”).
Claims 11 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20190228174 to Withrow et al. in view of U.S. Patent Application Publication No. 20210081698 to Lindeman et al. as applied to claim 1-3, 5-10, 12-14, and 17-19 above, and further in view of U.S. Patent Application Publication No. 20080031495 to Saijo et al.
With regards to claim 11, Withrow et al. fails to explicitly teach, but Saijo et al. teaches:
guiding a first user associated with the first product to capture an image of the first target frame, and output, to a device of the first user, information that prompts the capture of the image of the first target frame, or guide a second user to capture an image of the second target frame (paragraph [0103], “This allows the visual recognition of the relation in size between the detected image 6 and the target image 8. Recognizing such a display, a user is prompted to adjust the distance between the photographed subject 4 and the lens 24 of the cellular phone 76 so that the outline of the detected image 6 is matched to the target image 8.”),
output, to a device of the second user, information that prompts the capture of the image of the second target frame (paragraph [0104], “As in the case of FIG. 11, this allows the visual recognition of the relation in size between the detected image 6 and the target image 8. Recognizing such a display, the user is prompted to adjust the distance between the photographed subject 4 and the lens 24 of the cellular phone 76 so that the outline of the detected image 6 is matched to the target image 8.”).
This part of Saijo et al. is applicable to the system of Withrow et al. as they both share characteristics and capabilities, namely, they are directed to image based authentication processes. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Withrow et al. to include the imaging instructions as taught by Saijo et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Withrow et al. in order to provide image captures for objects that are optimized for authentication processes (see paragraphs [0027]-[0030] of Saijo et al.).
With regards to claim 16, Withrow et al. fails to explicitly teach, but Saijo et al. teaches:
acquire the second product information from a device of the second user (paragraph [0104], “As in the case of FIG. 11, this allows the visual recognition of the relation in size between the detected image 6 and the target image 8. Recognizing such a display, the user is prompted to adjust the distance between the photographed subject 4 and the lens 24 of the cellular phone 76 so that the outline of the detected image 6 is matched to the target image 8.”); and
update third product information related to the blank item related to a same type as the second product with the second product information (paragraph [0110], “When a comparison between the detected image 6 and the target image 8 demonstrates that the outline of the detected image 6 does not match the target image 8, an mismatching message indicating mismatching of both images is displayed (step S9). The process procedure then returns to step S3, from which steps S4 to S8 are executed again.”).
This part of Saijo et al. is applicable to the system of Withrow et al. as they both share characteristics and capabilities, namely, they are directed to image based authentication processes. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Withrow et al. to include the imaging instructions as taught by Saijo et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Withrow et al. in order to provide image captures for objects that are optimized for authentication processes (see paragraphs [0027]-[0030] of Saijo et al.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent Application Publication No. 2017/0300905 to Withrow et al. discusses a method to attempt authentication of an object comprises the steps of acquiring digital image data of at least a portion of an object by scanning a portion of the object; analyzing the image data to form a digital fingerprint of the object, wherein the digital fingerprint is responsive to the object itself and does not rely upon reading or recognizing information from any labels, tags, integrated materials, unique identification characters, codes, or other items that were added to the object for the purpose of identification; querying a database based on the digital fingerprint to obtain a result, wherein the database stores fingerprints from one or more known-authentic objects, and the result includes an indication as to whether the digital fingerprint matches a digital fingerprint stored in the database, and based on the result, triggering at least one predetermined action.
U.S. Patent Application Publication No. 2015/0371300 to Deyle et al. discusses a method for authenticating a good and determining if the good is in the seller's possession. It relies on a web-based authentication service that requires the seller to provide photos of key features specific to the item, along with an identification number, specific to the item that must be present in each photo. The present invention applies to goods sold either in person, in a retail store, or over the internet.
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/J.D.S./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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