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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 07/21/2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/21/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-4, 6, 7, and 12 are rejected under 35 U.S.C. 102a1 as being anticipated by US 2013/0329946 to Archibald et al, hereinafter “Archibald.”
With regard to claim 1, Archibald discloses a computer implemented method for detecting an output pose of interest of a subject in real-time [0077], the method comprising: recording at least one image frame of the subject using an imaging device([0077] - “one or more reference images”); determining an output pose of interest by processing the at least one image frame using a machine learning model that comprises a rule-based pose inference model ([0078]-[0079] - the first gesture model selected is prioritized over all other possible models) and a data-driven pose inference model ([0085] - a second gesture model selected via statistical methods), wherein with the data-driven pose inference model, determining a data-driven pose of interest by processing a single image frame of the subject, and wherein with the rule- based pose inference model, determining a rule-based output pose of interest by processing the same single image frame (the same image frame is used for both the first gesture model and the second gesture model [0085]); and determining as the output pose of interest the rule-based output pose of interest, if the rule- based pose inference model is able to determine the rule-based output pose of interest, otherwise determining the data-driven pose of interest as the output pose of interest (see [0081] where if the first gesture model (the rule-based model) is successful the detection ends, however, if the first gesture model fails, then a second gesture model (the data-driven model) is used to detect the gesture present in the one or more image frames).
With regard to claim 2, Archibald discloses the method according to claim 1, wherein a plurality of human key points is extracted from the image frame, and the human key points are processed by the machine learning model ([0042] - the multiple hand poses of Figure 3 and at [0063] with certain pixels detected that are likely gesture pixels (the “pixels” corresponding to the claimed key points).
With regard to claim 3, Archibald discloses the method according to claim 1, wherein the data-driven pose of interest is determined by determining a probability score for each of at least one predetermined pose of interest and outputting as the data-driven pose of interest that pose among the predetermined poses of interest that has the highest probability score [0085].
With regard to claim 4, Archibald discloses the method according to claim 1, wherein the rule-based pose of interest is determined by comparing pose descriptor data with at least one set of pose descriptors that uniquely define a predetermined pose of interest, and outputting as the rule-based pose of interest that pose among the predetermined poses of interest that matches with the pose descriptor data or outputting that no match was found if the pose descriptor data does not match any of the pose descriptors of any predetermined pose of interest ([0044] - a LUT is employed).
With regard to claim 6, Archibald discloses the method according to claim 1, wherein the output pose of interest is determined by a summation of weighted rule-based poses of interest with the data-driven pose of interest, wherein the weight of the rule-based pose of interest that was determined to be in the image frame is set to 1 and the weight of the data-driven pose of interest is set to 0 ([0081] - where if the first gesture models returns a gesture (weighted at 1), the second gesture model is never used (weighted at 0).
With regard to claim 7, Archibald discloses the method according to claim 1, wherein no output pose of interest is determined, if the certainty determined for the presence of a predetermined pose of interest in the image frame is below a predetermined threshold ([0067] - 8 cascaded stages are used, and if all 8 fail to return a gesture, then it is determined that no gesture is present).
Claim 12 is rejected for reasoning, mutatis mutandis, as that of claim 1 above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 5, 8-11, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Archibald in view of US 10,452,933 to Chan et al, hereinafter “Chan.”
Archibald discloses a gesture recognition process that employs multiple gesture models as noted above (a first, rule-based model that is prioritized and a second, data driven model using probability statistics). However, with regard to claims 8-11 and 13, Archibald fails to disclose the environment of the gestures being in or around a vehicle (i.e. driver or pedestrian) and used to impact control of the vehicle; and Archibald also fails to disclose the use of a Euclidean distance (claim 5) for determining the human pose points in the data-driven second gesture model.
On the other hand, Chan discloses in the same field of endeavor (gesture recognition, see Figure 1) a process for determining gestures of drivers and/or pedestrians that can subsequently transfer control from the driver to the vehicle, see col 4, line 51-62, and col 5, lines 52-63.
Therefore, it would have been obvious before the effective filing date of the claimed invention to have used the gesture recognition process taught by Archibald in a vehicular environment (driver/pedestrians) as taught by Chan as doing this would ensure that quick recognition of gestures takes place in the ever-changing dynamic vehicular landscape. See Archibald at [0002] - “desirable then to implement gesture detection methods that are less time-consuming and more power efficient.”
In addition, Archibald fails to disclose the Euclidean distance calculation for assisting in determining the gesture (claim 5). However, Chan discloses in col 16, lines 37-56 the use of skeletal diagrams (key points, see Figure 1) where the Euclidean distance is found between points.
Therefore, it would have been further obvious before the effective filing date of the claimed invention to have used the Euclidean distance technique of gesture recognition taught by Chan in the gesture recognition process taught by Archibald with the reasoning being that the Euclidean distance calculation is simple to perform and also permits fast computation (i.e. reduces load on the processor) which is needed when analyzing videos of drivers and pedestrians in an ever changing vehicular environment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID OMETZ whose telephone number is (571)272-7593. The examiner can normally be reached M-F, 8am-4pm.
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DAVID OMETZ
Primary Examiner
Art Unit 2672
/DAVID OMETZ/Primary Examiner, Art Unit 2672
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