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 Arguments
Applicant’s arguments filed on 12/11/2025, with respect to claims 2, 5, 8, 13-14, 16-17, and 19, have been fully considered and are persuasive. The rejection of said claims has been withdrawn and are indicated as allowable.
Applicant's arguments filed on 12/11/2025, with respect to independent claims 1, 12, and 15, have been fully considered but they are not persuasive. Regarding independent claims Applicant argues that “The cited portions of Tian do not teach or disclose "determining if the asset feature of the candidate 3D object matches an authentic asset feature of at least one authentic 3D object" let alone "if the asset feature of the candidate 3D object matches the authentic asset feature of the at least one authentic 3D object, classifying the candidate 3D object as an inauthentic object" or "if the asset feature of the candidate 3D object does not match the authentic asset feature of the at least one authentic 3D object, classifying the candidate 3D object as an authentic object" (emphasis added) as recited in claim 1. Explained another way, at the cited portions and elsewhere, Tian discloses "whether or not the face in the image is authentic based on face liveness" whereas claim 1 is directed to "determining if the asset feature of the candidate 3D object matches an authentic asset feature of at least one authentic 3D object." (emphasis added) Applicant respectfully submits that the determination of "whether or not the face in the image is authentic based on “face Response liveness" is different from "determining if the asset feature of the candidate 3D object matches an authentic asset feature of at least one authentic 3D object" as recited in claim 1” (please see Remarks, page 9 and page 10).
Examiner respectfully disagrees, as previously cited Tian reference in paragraph 71 discloses “The liveness determination section 230 determines whether or not the face in the image is authentic based on face liveness (Score in Equation (11) or (13)). When Score is equal to or more than a threshold value T, the detection target is determined to be a real object and thus authentic. When Score is equal to or less than T, the detection target is determined to be not authentic. Here, the threshold value T may be changed depending on the number of feature points used to obtain the evaluation value Score”, here please note here detection target i.e., face in the image corresponds to claimed “ candidate 3D object” and feature points corresponds to claimed “authentic asset feature of the candidate 3D object”. Hence from paragraph 71, it is clear when Score is equal to or less than T, the detection target is determined to be not authentic and When Score is equal to or more than a threshold value T, the detection target is determined to be a real object and thus authentic. Therefore as can be seen from above explanation Tian reference reads on the argued limitations as presented by the Applicant. Examiner suggests Applicant to further elaborate on “candidate 3D object” and/or “authentic asset feature” in the claims if different from the cited reference to overcome the cited reference.
Regarding claim 7, Applicant argues that “The cited portions of Dal do not teach or suggest "adjusting a camera view during capture of the image such that the candidate 3D object occupies at least a specified area of the image" per claim 7.
Explained another way, the cited portions of Dal disclose "rectify[ing] input images" suggesting that the cited portions of Dal are directed to already captured images whereas claim 7 recites "adjusting a camera view during capture of the image." Additionally, the cited portions of Dal are silent as to "the candidate 3D object occup[ying] at least a specified area of the image" as recited in claim 7.” (please see Remarks, page 15).
Examiner respectfully disagrees, as cited paragraph 99 of Dal discloses “camera calibration information can provide information to rectify input images so that epipolar lines of the equivalent camera system are aligned with the scanlines of the rectified image. In such a case, a 3-D point in the scene projects onto the same scanline index in the master and in the slave image. Let u.sub.m and u.sub.s be the coordinates on the scanline of the image of the same 3-D point p in the master and slave equivalent cameras, respectively”, hence in order to capture images (input image) camera perform calibration (i.e., claimed adjusting a camera view) so that 3D object occupies predetermined area of the image. Therefore, Dal discloses the argued limitation as presented by the Applicant.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim(s) 1, 3-4, 7, 11-12, 15, 18, and 20, is/are rejected under 35 U.S.C. 103 as being unpatentable over Dal (US PGPUB 2019/0108396 A1) and further in view of An (US PGPUB 2015/0154229 A1) and further in view of Tian (US PGPUB 2016/0379050 A1).
As per claim 1, Dal discloses a computer-implemented method (Dal, Figs. 1-12), comprising:
generating a plurality of images of a candidate 3D object, wherein each image of the plurality of images of the candidate 3D object is from a respective camera position of two or more camera positions (Dal, paragraphs 84, 197, 245 and 247);
Dal does not explicitly disclose determining one or more histogram of oriented gradients (HOG) vectors for each image of the plurality of images of the candidate 3D object;
determining an asset feature of the candidate 3D object based on the one or more HOG vectors for each of the plurality of images of the candidate 3D object;
An discloses determining one or more histogram of oriented gradients (HOG) vectors for each image of the plurality of images of the candidate 3D object (An, paragraph 59, discloses HOG);
determining an asset feature of the candidate 3D object based on the one or more HOG vectors for each of the plurality of images of the candidate 3D object (An, paragraph 126, discloses For each face part, small patches such as 8 by 8 small patches are extracted and for each patch, a HOG feature vector is extracted with the number of orientation bins being set to 31. Such image representations are robust to face pose and expression variations);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Dal teachings by identifying objects, as taught by An.
The motivation would be to provide an improved object identification system (paragraph 112), as taught by An.
Dal in view of An does not explicitly disclose determining if the asset feature of the candidate 3D object matches an authentic asset feature of at least one authentic 3D object;
if the asset feature of the candidate 3D object matches the authentic asset feature of the at least one authentic 3D object, classifying the candidate 3D object as an inauthentic object; and
if the asset feature of the candidate 3D object does not match the authentic asset feature of the at least one authentic 3D object, classifying the candidate 3D object as an authentic object.
Tian discloses determining if the asset feature of the candidate 3D object matches an authentic asset feature of at least one authentic 3D object (Tian, Fig. 3:3, and paragraph 71);
if the asset feature of the candidate 3D object matches the authentic asset feature of the at least one authentic 3D object, classifying the candidate 3D object as an inauthentic object (Tian, Fig. 3:3, and paragraph 71, discloses When Score is equal to or less than T, the detection target is determined to be not authentic); and
if the asset feature of the candidate 3D object does not match the authentic asset feature of the at least one authentic 3D object, classifying the candidate 3D object as an authentic object (Tian, Fig. 3:3, and paragraph 71, discloses When Score is equal to or less than T, the detection target is determined to be not authentic).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Dal in view of An teachings by authenticating object, as taught by Tian.
The motivation would be to provide an improved system with high accuracy and through a simple process (paragraph 14), as taught by Tian.
As per claim 3, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 1, wherein determining if the asset feature of the candidate 3D object matches an authentic asset feature of at least one authentic 3D object comprises performing a rotationally invariant comparison of the asset feature of the candidate 3D object and the authentic asset feature of the at least one authentic 3D object (Dal, paragraph 247, discloses use of max-pooling to mitigate some of the pose invariance issues described above. In some embodiments of the present invention, the selection of particular poses of the virtual cameras, e.g., the selection of which particular 2-D views to render, results in a descriptor F having properties that are invariant. For example, considering a configuration where all the virtual cameras are located on a sphere (e.g., all arranged at poses that are at the same distance from the center of the 3-D model or a particular point p on the ground plane, and all having optical axes that intersect at the center of the 3-D model or at the particular point p on the ground plane). Another example of an arrangement with similar properties includes all of the virtual cameras located at the same elevation above the ground plane of the 3-D model, oriented toward the 3-D model (e.g., having optical axes intersecting with the center of the 3-D model), and at the same distance from the 3-D model, in which case any rotation of the object around a vertical axis (e.g., perpendicular to the ground plane) extending through the center of the 3-D model will result in essentially the same vector or descriptor F (assuming that the cameras are placed at closely spaced locations)).
As per claim 4, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 3, wherein performing the rotationally invariant comparison of the asset feature of the candidate 3D object and the authentic asset feature of the at least one authentic 3D object comprises:
generating a plurality of rolled asset feature vectors of the candidate 3D object based on the asset feature of the candidate 3D object, wherein each rolled asset feature vector corresponds to a particular orientation of the candidate 3D object (Dal, paragraph 247); and
comparing each of the plurality of rolled asset feature vectors with the authentic asset feature of the at least one authentic 3D object (Dal, paragraph 247).
As per claim 7, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 1, wherein generating the image of the candidate 3D object comprises adjusting a camera view during capture of the image such that the candidate 3D object occupies at least a specified area of the image (Dal, paragraph 99).
As per claim 11, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 1, further comprising performing principal component analysis of the asset feature to reduce a dimension of the asset feature (Dal, paragraph 225), and wherein determining if the asset feature of the candidate 3D object matches the authentic asset feature of at least one authentic 3D object comprises performing a comparison of a reduced dimension asset feature of the candidate 3D object against a reduced dimension authentic asset feature of the at least one authentic 3D object (Dal, paragraph 225).
As per claim 12, Dal discloses a non-transitory computer-readable medium comprising instructions that, responsive to execution by a processing device, causes the processing device to perform operations (Dal, paragraphs 6 and 124) comprising:
For rest of claim limitations please see the analysis of claim 1.
As per claim 15, Dal discloses a system (Dal, Figs. 1-12) comprising:
a memory with instructions stored thereon (Dal, paragraphs 6 and 124); and
a processing device, coupled to the memory, the processing device configured to access the memory and execute the instructions (Dal, paragraphs 6 and 124-125), wherein the instructions cause the processing device to perform operations (Dal, paragraphs 6 and 124-125) including:
For rest of claim limitations please see the analysis of claim 1.
As per claim 18, please see the analysis of claim 3.
As per claim 20, please see the analysis of claim 11.
Claim(s) 6, is/are rejected under 35 U.S.C. 103 as being unpatentable over Dal (US PGPUB 2019/0108396 A1) and further in view of An (US PGPUB 2015/0154229 A1) and further in view of Tian (US PGPUB 2016/0379050 A1) and further in view of Selviah (US PGPUB 2023/0146134 A1).
As per claim 6, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 1, wherein generating the plurality of images of the candidate 3D object comprises Dal in view of An in view of Tian does not explicitly disclose generating the plurality of images at one or more azimuth and elevation points.
Selviah discloses generating the plurality of images at one or more azimuth and elevation points.(Selviah, paragraph 130).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Dal in view of An in view of Tian teachings by generating image data, as taught by Selviah.
The motivation would be to provide an improved classification system with reduction in processing cost (paragraph 18), as taught by Selviah.
Claim(s) 9-10, is/are rejected under 35 U.S.C. 103 as being unpatentable over Dal (US PGPUB 2019/0108396 A1) and further in view of An (US PGPUB 2015/0154229 A1) and further in view of Tian (US PGPUB 2016/0379050 A1) and further in view of Mayes (US PGPUB 2021/0174132 A1).
As per claim 9, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 1, wherein classifying the candidate 3D object as the authentic object further comprises Dal in view of An in view of Tian does not explicitly disclose assigning a flag to the candidate 3D object, and wherein the flag is readable by a game engine and causes the game engine to enable use of the candidate 3D object in a virtual environment hosted by the game engine.
Mayes discloses assigning a flag to the candidate 3D object, and wherein the flag is readable by a game engine and causes the game engine to enable use of the candidate 3D object in a virtual environment hosted by the game engine (Mayes, paragraphs 20, 128, and 133).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Dal in view of An in view of Tian teachings by generating image data, as taught by Mayes.
The motivation would be to provide an improved system for identifying and labeling authentic objects (paragraph 91), as taught by Mayes.
As per claim 10, Dal in view of An in view of Tian further discloses the computer-implemented method of claim 1, wherein classifying the candidate 3D object as the inauthentic object further comprises Dal in view of An in view of Tian does not explicitly disclose assigning a flag to the candidate 3D object, and wherein the flag is readable by a game engine and causes the game engine to prevent use of the candidate 3D object in a virtual environment hosted by the game engine.
Mayes discloses assigning a flag to the candidate 3D object, and wherein the flag is readable by a game engine and causes the game engine to prevent use of the candidate 3D object in a virtual environment hosted by the game engine (Mayes, paragraphs 20, 128, and 133).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Dal in view of An in view of Tian teachings by generating image data, as taught by Mayes.
The motivation would be to provide an improved system for identifying and labeling authentic objects (paragraph 91), as taught by Mayes.
Allowable Subject Matter
Claim 2, 5, 8, 13-14, 16-17, and 19, are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYED Z HAIDER whose telephone number is (571)270-5169. The examiner can normally be reached MONDAY-FRIDAY 9-5:30 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SAM K Ahn can be reached at 571-272-3044. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SYED HAIDER/Primary Examiner, Art Unit 2633