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 .
Applicant’s response to the Non-Final Office Action dated 12/29/2025, filed with the office on 03/26/2026, has been entered and made of record.
Status of Claims
Claims 1-6, 8-15, and 17-22 are pending. Claims 21-22 are new. Claims 7 and 16 are cancelled.
Response to Amendments
In light of Applicant’s amendments, the objections of record with respect to claim 7 is withdrawn.
In light of the Applicant’s amendments of claim 4 the 112(b) rejections of record for indefiniteness has been withdrawn.
Response to Arguments
Applicant’s amendments of independent claims 1, 10, and 19 which has altered the scope of the claims of the instant application, has necessitated the new ground(s) of rejection presented in this office action with respect to claims of the instant application. Accordingly, in response to Applicant’s arguments that are merely directed to the amended portion of the claims, new analyses have been presented below, which make Applicant’s arguments moot.
Consequently, THIS ACTION IS MADE FINAL.
Claim Objections
Claim 13 is objected to because of the following informality:
Claim 13 recites “matches to a certain level or higher with the…” should be “meets or exceeds a matching probability value threshold…”. Please correct claim 13 to match the amendments of claim 4.
Appropriate corrections are required.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 8-15, and 17-22 are rejected under 35 U.S.C. 103 as being unpatentable over Choi et al. (KR20210155283A - From IDS, machine translation from Espacenet) in view of Meany et al. (WO 2022/221327A1).
Regarding claim 10, Choi teaches “An electronic device (Choi paragraph [0047] "An electronic device (100)") comprising:
memory storing one or more programs (Choi paragraph [0056] "The memory (140) can store various data, programs or applications for driving and controlling the electronic device (100)");
one or more processors (Choi paragraph [0047] "An electronic device (100) according to one embodiment may include a sensing unit (110), a communication unit (120), a processor (130)"); and
a sensing module including at least one sensor (Choi paragraph [0048] "The sensing unit (110) may include various sensors"), wherein the one or more programs include computer-executable instructions that, when executed by the one or more processors (Choi paragraph [0056] "A program (one or more instructions) or application stored in memory (140) can be executed by the processor (130)"), cause the electronic device to:
recognize, by using an object recognition model, an object belonging to a space (Choi paragraph [0032] "can move through an entire space (e.g., an entire shopping mall) and, using a first recognition model among a plurality of recognition models, detect objects existing in the entire space and obtain object information (location information and classification information of the objects) for the detected objects") from space scan information for the space, the space scan information being obtained by using the sensing module (Choi paragraph [0048] "The sensing unit (110) may include various sensors configured to sense information about the surrounding environment of the electronic device (100) […] the sensing unit (110) can obtain spatial structure information for a given space by using at least one of a camera, an ultrasonic sensor, and a lidar sensor"), label object information of the object on an area recognized as the object in the space scan information based on an object recognition result of the object recognition model (Choi paragraph [0077] "object information obtained by an electronic device (100) according to one embodiment using a first recognition model can be displayed on a spatial map for the entire space. At this time, the position of the displayed mark can be determined based on the position information of the recognized object included in the object information. Additionally, the shape of the mark can be determined based on the classification information (e.g., type) of the recognized object included in the object information"),
generate a spatial map for the space based on the space scan information (Choi paragraph [0027] "The electronic device (100) can generate a spatial map (10-1) for the shopping mall based on the acquired spatial structure information") and the object information for the object belonging to the space (Choi paragraph [0032] "the electronic device (100) according to one embodiment can divide the space into a plurality of subset spaces based on the acquired object information. For example, the electronic device (100) can logically divide the space based on the location information of the recognized object in the entire space and the classification information of the recognized object").“
However, Choi is not relied on to teach “when there is an object unrecognizable through the object recognition model in the space scan information, obtain, by using a feature analysis model, feature information relating to an object unrecognizable through an-the object recognition model from the space scan information labeled according to a result of the object recognition model, identify the object unrecognizable through the object recognition model, by using a query of a personalized database based on the obtained feature information”.
Meany teaches “when there is an object unrecognizable through the object recognition model in the space scan information (Meany paragraph [0039] "Some parts may be easily identified by visual inspection 12 from information imprinted on the surface, prior experience, distinctive shape, size, etc. […] However, many [items/parts] are not readily identifiable, perhaps due to uncommon brand, outdated product, damaged/dirty condition, missing information tag, or unfamiliarity"), obtain, by using a feature analysis model, feature information relating to an object unrecognizable through an-the object recognition model from the space scan information labeled according to a result of the object recognition model (Meany paragraph [0039] "In such a case, the user captures the part parameters with a 3D imaging device at 20. The part parameters do not have to be complete. A partial part can be submitted for scanning, or a partial scan of the part can be utilized. The resulting scan data can be transmitted at 22 to a computerized recognition system that resides either locally or on a remote network"), identify the object unrecognizable through the object recognition model, by using a query of a personalized database based on the obtained feature information (Meany paragraph [0039-0040] "The resulting scan data can be transmitted at 22 to a computerized recognition system that resides either locally or on a remote network, or can be transmitted at 22 via transportable device capable of storing said resulting scan data, such as a thumb drive, external hard drive, removable hard drive, or any type of device that can be connected to the computerized recognition system. The data is then processed to extract a profile consisting of geometric and photometric descriptors 24 suitable for part identification. The computerized recognition system compares this profile against a corresponding database 40 of previously acquired profiles, eliminates very unlikely matches 28, and ranks surviving candidate profiles according to match likelihood. The associated identifiers (e.g., part numbers) for the best matches, along with their likelihoods, are returned and presented to the user")”.
It would have been obvious to a person having ordinary skill in the art before
effective filing date of the claimed invention of the instant application to combine an
an electronic device that generates spatial map of a space and identifies objects as taught by Choi to use the object recognition model and feature extraction method as taught by Meany.
The suggestion/motivation for doing so would have been “The computerized system of the present disclosure can remove non-matches from a first result set, or a candidate match list provided by a system or application outside of the computerized system, to improve the accuracy of the objects listed in the candidate list and reduce bad or improper candidates captured in the candidate list" as noted by the Meany disclosure in paragraph 57. One having ordinary skill in the art would recognize having accurate object detection would lead to having accurate spatial map by including details of the identified objects.
Therefore, it would have been obvious to combine the disclosure of Choi with
the Meany disclosure to obtain the invention as specified in claim 10 as there is a
reasonable expectation of success and/or because doing so merely combines prior art
elements according to known methods to yield predictable results.
Claim 1 recites a method with steps corresponding to the device elements
recited in claim 10. Therefore, the recited steps of this claim are mapped to the
proposed combination in the same manner as the corresponding elements of device
claim 10. Additionally, the rationale and motivation to combine the Choi and Meanly
references, presented in rejection of claim 10 apply to this claim.
Regarding claim 2 (similarly claim 11 and claim 20), the combination of Choi and Meanly teaches “The method of claim 1, wherein the identifying comprises:
obtaining information about object candidates from the personalized database, in response to the query (Meany paragraph [0040] "The data is then processed to extract a profile consisting of geometric and photometric descriptors 24 suitable for part identification");
comparing estimated image information of the object unrecognizable through the object recognition model with image information of each object included in the object candidates (Meany paragraph [0040] "The computerized recognition system compares this profile against a corresponding database 40 of previously acquired profiles, eliminates very unlikely matches 28, and ranks surviving candidate profiles according to match likelihood"); and
identifying, based on a result of the comparing, the object unrecognizable through the object recognition model (Meany paragraph [0040] "The associated identifiers (e.g., part numbers) for the best matches, along with their likelihoods, are returned and presented to the user").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 2. Finally the method recited in claim 2 is met by Choi and Meany.
Regarding claim 3 (similarly claim 12), the combination of Choi and Meanly teaches “The method of claim 2, wherein the obtaining of the information about object candidates comprises: comparing the feature information included in the query with property information of each object stored in the personalized database (Meany paragraph [0040] "The computerized recognition system can extract photometric descriptors and/or features to eliminate many of the possible matches that are not the correct size, shape, proportions, etc.") to obtain the information about the object candidates having property information corresponding to the feature information (Meany paragraph [0040] " The computerized system can further refine and generate a candidate match list that is a subset of the initial candidate list which can comprise a single best match, a set of likely matches, or a set from which the most unlikely matches have been removed").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 3. Finally the method recited in claim 3 is met by Choi and Meany.
Regarding claim 4 (similarly claim 13), the combination of Choi and Meanly teaches “The method of claim 2, wherein the query is a request to collect object information about at least one object whose property information for each object stored in the personalized database meets or exceeds a matching probability value threshold (Meany paragraph [0011] "determine a score, probability, or other degree of similarity between the query object and each of the learned models in the database; similarity can be determined using any of a number of approaches, such as exhaustive comparison, indexing/hashing, bag-of-words retrieval, application of a classifier, or propagation through a neural network. The system then reports an ordered list of the top matching labels and their associated scores") with the obtained feature information (Meany paragraph [0063] "Fig. 8 shows a screenshot 110 of potential matching parts and information about the matching parts, such as price, part number, inventory quantity available, name of the part, size of the part, dimensions of the part, or any other information that the database 40 comprises about the matching part, retrieved from a search through the database 40 in the system memory, preferably, in the preferred embodiment, ranking down from the highest match percentage").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 4. Finally the method recited in claim 4 is met by Choi and Meany.
Regarding claim 5 (similarly claim 14), the combination of Choi and Meanly teaches “The method of claim 2, wherein the identifying of the object unrecognizable through the object recognition model based on the result of the comparing comprises:
shifting a location of the electronic device including the at least one sensor to a certain viewpoint (Choi paragraph [0045] "the electronic device (100) can perform object recognition by loading a second recognition model into a first computing unit while moving through a first subset space"); and
generating estimated image information of the object unrecognizable through the object recognition model, by using the at least one sensor, at the shifted location (Meany paragraph [0040] "The data is then processed to extract a profile consisting of geometric and photometric descriptors 24 suitable for part identification. The computerized recognition system compares this profile against a corresponding database 40 of previously acquired profiles, eliminates very unlikely matches 28, and ranks surviving candidate profiles according to match likelihood. The associated identifiers (e.g., part numbers) for the best matches, along with their likelihoods, are returned and presented to the user").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 5. Finally the method recited in claim 5 is met by Choi and Meany.
Regarding claim 8 (similarly claim 17), the combination of Choi and Meanly teaches “The method of claim 1, further comprising: updating the personalized database (Meany paragraph [0051] "database: a digital catalog or repository of parts, along with their identifiers and profiles, that can be queried according to various attributes, and can be concatenated, augmented, or updated with data from previous queries"), based on the space scan information and the object information for the object belonging to the space, wherein the generating of the spatial map for the space comprises generating the spatial map for the space, based on the updated personalized database (Choi paragraph [0032] "can move through an entire space (e.g., an entire shopping mall) and, using a first recognition model among a plurality of recognition models, detect objects existing in the entire space and obtain object information (location information and classification information of the objects) for the detected objects").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 8. Finally the method recited in claim 8 is met by Choi and Meany.
Regarding claim 9 (similarly claim 18), the combination of Choi and Meanly teaches “The method of claim 1, wherein the personalized database (Meany paragraph [0051] "database: a digital catalog or repository of parts, along with their identifiers and profiles, that can be queried according to various attributes, and can be concatenated, augmented, or updated with data from previous queries") registers property information of each object belonging to assets of a user for each object (Choi paragraph [0036] "As shown in the space map (10-3) of Fig. 1c, for the first subset space (11) classified into the “electronic products” group, object recognition can be performed using a second recognition model that can be classified into subclasses of electronic products"), and wherein the property information comprises model-property information determined in a production process of an object and use-property information determined in a use process of the user (Choi paragraph [0036] "For example, the second recognition model may be, but is not limited to, a model that can classify objects into subclasses of electronic products, such as TVs, refrigerators, gas ranges, ovens, washing machines, dryers, vacuum cleaners, and computers").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 9. Finally the method recited in claim 9 is met by Choi and Meany.
Regarding claim 15 (similarly claim 6), the combination of Choi and Meanly teaches “The electronic device of claim 11, further comprising: a communication module (Choi paragraph [0049] "communication unit (120)"), wherein the one or more programs further include computer-executable instructions that, when executed by the one or more processors, cause the electronic device to:
receive information about object candidates from a cloud server as a response to transmitting the query to the cloud server including the personalized database, through the communication module (Choi paragraph [0049] "The communication unit (120) can transmit and receive data or signals with an external device (e.g., a server) under the control of the processor (130)").”
Claim 19 recites a computer readable medium including computer executable instructions corresponding to the elements of the device recited in claim 10. Therefore, the recited instructions of the computer readable medium of claim 19 are mapped to the proposed combination in the same manner as the corresponding elements of the device claim 10. Additionally, the rationale and motivation to combine Choi and Meany presented in rejection of claim 10, apply to this claim. Finally, the combination of Choi and Meany teaches “One or more non-transitory computer-readable storage media storing one or more programs including computer-executable instructions that, when executed by one or more processors of an electronic device, cause the electronic device to perform operations (for example, Choi paragraph [0138] "electronic device according to one embodiment may be implemented in the form of program commands that can be executed through various computer means and recorded on a computer-readable medium")”.
Regarding claim 21, the combination of Choi and Meany teaches “The method of claim 1, wherein the feature analysis model extracts information about an image, color, or size of the area corresponding to the object unrecognizable through the object recognition model in the labeled space scan information as feature information (Meany paragraph [0039 - 0040] "Some parts may be easily identified by visual inspection 12 from information imprinted on the surface, prior experience, distinctive shape, size, etc. If such is present, and the part is visually identifiable 14, then one merely verifies that the part is correct in step 16, and takes action, ordering the proper part at 18. However, many are not readily identifiable, perhaps due to uncommon brand, outdated product, damaged/dirty condition, missing information tag, or unfamiliarity. In such a case, the user captures the part parameters with a 3D imaging device at 20. The part parameters do not have to be complete. A partial part can be submitted for scanning, or a partial scan of the part can be utilized […] The computerized recognition system can extract photometric descriptors and/or features to eliminate many of the possible matches that are not the correct size, shape, proportions, etc").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 21. Finally the method recited in claim 21 is met by Choi and Meany.
Regarding claim 22, the combination of Choi and Meany teaches “The method of claim 1, wherein a cloud server stores space scan information from a plurality of electronic devices (Meany paragraph [0044] "the electronic device 100, the butler robot 300-1, the pet robot 300-2 and the smart home camera 300-3 may transmit the space scan information or object information, or the spatial map to the cloud server 200 to store and manage the space scan information or object information or the spatial map through the cloud server 200"), and wherein the space scan information from a plurality of electronic devices is managed by the personalized database (Meany paragraph [0076] "As the task of the electronic device 100 to be performed in the space is influenced by objects located in the space, the cloud server 200 may store and manage the object information for the objects located in the space in a database. The database may register and store the object information such as the object's identification information and property information for each object. The object information stored in the database may be used not only to generate a spatial map but also to identify an object unrecognizable through an object recognition model from the space scan information").”
The proposed combination as well as the motivation for combining Choi and Meany references presented in the rejection of claim 10, applies to claim 22. Finally the method recited in claim 22 is met by Choi and Meany.
Reference Cited
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US Publication US20140279860 A1 to Pan et al. discloses a method of using a spatial map recognizing objects belonging to the space using a personalized database.
Conclusion
THIS ACTION IS MADE FINAL. 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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/JASPREET KAUR/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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