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 .
Notice re prior art available under both pre-AIA and AIA
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 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.
Examiner's Note
Examiner has cited particular columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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 1-4 are rejected under 35 U.S.C. 103 as being unpatentable over Hilbert, et al. (US 11,704,965 B2) in view of Hwan, et al. (Computer English Translation of Korean Patent Number KR 10-0815291 B1).
With regard to claim 1, Hilbert, et al. (hereinafter “Hilbert”) discloses an information processing apparatus for pixels may then be analyzed using one or more suitable image analysis techniques to detect any faces and, if a face is detected, an identity of a player associated with the face. The remaining pixels from the captured image may be ignored to reduce the computational resource cost of player tracking (See for example, col. 4, lines 58-63), Hilbert does not expressly call for the above crossed-out limitations. However, Hwan, et al. (See for example, page 11, lines 30 - page 12, line 7. Please note, detecting overfitting of a machine learning model is implied by the description made in page 7, lines 3-8 “According to the present invention, by reflecting a different usage pattern for each user through reinforcement learning by feedback by the user, by providing a face recognizer having a parameter optimized according to the user to provide a face of the person included in the digital data with significantly high accuracy There is an effect that can be recognized. In addition, according to the present invention, through the reinforcement learning by the feedback of the user can provide a face detector that can adjust the threshold value that can be determined as a face and have an optimized parameter, so that It has the effect of detecting the face area.”) teach this feature. Hilbert and Hwan, et al. are combinable because they are from the same field of endeavor, i.e., face detection using reinforcement learning (page 7, lines 6-8). Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to incorporate the teaching as taught by Hwan, et al. into the system of Herbert, and to do so would at least allow automatically optimizing a parameter of a face detector using feedback of a user to increase a detection rate of a face area of at least one person included in generated digital data (See for example, page 3, lines 19-20). Therefore, it would have been obvious to combine Herbert with Hwan, et al. to obtain the invention as specified in claim 1.
With regard to claim 2, the information processing apparatus according to claim 1, wherein the machine learning model detects a plurality of objects including the first object and the second object in the input image, and determining whether or not the first object is detected again includes executing the object detection process in the mask image, and determining whether or not the first object is detected again, the mask image obtained by invalidating (via excluding some or all of the faces associated with bystanders) the image features distributed in a second object region, i.e., the region occupied by the bystanders, indicating a region of the second object and a region different from the first object region in the basis region (See for example, col. 15, lines 41-57; and Figs. 8-11 of Herbert) .
With regard to claim 3, the information processing apparatus according to claim 1, wherein the machine learning model detects the plurality of objects including the first object and the second object in the input image, and determining whether or not the first object is detected again includes executing the object detection process in the mask image, and determining whether or not the first object is detected again, the mask image obtained by invalidating the image features distributed in the second object region indicating the region of the second object in the basis region (See for example, col. 15, lines 41-57; and Figs. 8-11 of Herbert).
With regard to claim 4, the information processing apparatus according to claim 1, wherein the one or more commands further cause the information processing apparatus to repeat specifying the basis region and determining whether or not the first object is detected again, while changing the predetermined threshold value or the first object (See for example, Fig. 12 of Herbert, wherein the fisheye appearance in which the objects within the captured image are changed via a de-warping process).
Allowable Subject Matter
Claims 5 and 6 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US Patent Application Publication Number 2022/0164602.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL G MARIAM whose telephone number is (571)272-7394. The examiner can normally be reached M-F 7:30-5:00 EST.
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/DANIEL G MARIAM/ Primary Examiner, Art Unit 2675