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 .
This office action is in response to communication fled on 6/11/2026. Claims 1-20 are pending on this application.
Response to Arguments
Applicant’s arguments, see Remarks, filed 6/11/2026, with respect to the rejection(s) of claim(s) 1-20 under 35 US 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Pittaluga et al (US20220067457) in view of McMackin et al (US20120038819) and Khadloya et al (US20220292902).
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) 1-6, 8-13, and 15-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pittaluga et al (US20220067457) in view of McMackin et al (US20120038819) and Wu et al (US20220024415).
Regarding claim 1, Pittaluga teaches a method for image privacy protection and actionable response (para. [0004]), comprising:
distorting a captured analog image using a transform filter (para. [0021], First, privacy processing must occur prior to image capture, via optical filtering; para. [0029]); and
analyzing the distorted image using a trained machine learning process (para. [0029], The utility networks learned in the training step can be used to estimate the public attributes from the encoded images).
Pittaluga fails to teach digitizing the distorted analog image.
However McMackin teaches distorting a captured analog image (par. [0112], a filter may be placed in front of the light sensing device 130 to restrict the modulated light stream to a specific range of wavelengths or polarization) and digitizing the distorted analog image (140 in fig. 2A; para. [0100], [0104]).
Therefore taking the combined teachings of Pittaluga and McMackin as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the steps of McMackin into the method of Pittaluga. The motivation to combine McMackin and Pittaluga would be to achieve better compression (para. [0149] of McMackin).
The modified method of Pittaluga fails to teach analyzing the distorted, digitized image using a trained machine learning process to identify at least one of an individual or an object in the distorted, digitized image, the machine learning process having been trained to identify individuals and objects in the distorted image; and
upon identification of at least one of an individual or an object in the distorted, digitized image for which an action is to be taken, communicating an indication to at least one device to cause the at least one device to perform a predetermined action.
However Wu teaches analyzing a digitized image using a trained machine learning process to identify at least one of an individual or an object in the digitized image (para. [0096], an object detection network may be employed to perform object detection on at least one image in the video stream, wherein the object detection network may be based on a deep learning architecture), the machine learning process having been trained to identify individuals (para. [0088]) and objects in the image (para. [0096]); and
upon identification of at least one of an individual or an object in the digitized image for which an action is to be taken (para. [0084]-[0085]), communicating an indication to at least one device to cause the at least one device to perform a predetermined action (para. [0111]-[0112]).
Therefore taking the combined teachings of modified Pittaluga and Wu as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the steps of Wu into the method of modified Pittaluga. The motivation to combine Wu and modified Pittaluga would be to accurately determine the door-opening intention of a person (para. [0082] of Wu).
Regarding claim 2, the modified method of Pittaluga teaches a method wherein the transform filter comprises at least one of a Walsh-Hadamard transform or a Fourier transform (para. [0039] of Pittaluga; para. [0009] of McMackin).
Regarding claim 3, the modified method of Pittaluga teaches a method wherein the analog image is captured using an image capture device located in at least one of a residential, a commercial, or an industrial environment (para. [0073] of Pittaluga).
Regarding claim 4, the modified method of Pittaluga teaches a method wherein the at least one device is located in the at least one residential, commercial or industrial environment (para. [0073] of Pittaluga) and the predetermined action performed by the at least one device causes a change to the at least one residential, commercial, or industrial environment (para. [0111]-[0112] of Wu. It would be obvious to apply the actions to the environments of Pittaluga).
Regarding claim 5, the modified method of Wu teaches a method further comprising:
determining a status of the at least one individual or object identified (para. [0040]-[0041] of Wu) in the distorted, digitized image (para. [0100], [0104] of McMackin) for which action is to be taken (para. [0084] of Wu).
Regarding claim 6, the modified method of Wu teaches a method wherein a predetermined action to be taken by the device is dependent on the determined status of the at least one individual or object identified in the distorted, digitized image for which action is to be taken (para. [0040]-[0041] and [0084] of Wu).
Regarding claim 8, the claim recites similar subject matter as claim 1 and is rejected for the same reasons as stated above.
Regarding claim 9, the claim recites similar subject matter as claim 2 and is rejected for the same reasons as stated above.
Regarding claim 10, the claim recites similar subject matter as claim 3 and is rejected for the same reasons as stated above.
Regarding claim 11, the claim recites similar subject matter as claim 4 and is rejected for the same reasons as stated above.
Regarding claim 12, the claim recites similar subject matter as claim 5 and is rejected for the same reasons as stated above.
Regarding claim 13, the claim recites similar subject matter as claim 6 and is rejected for the same reasons as stated above.
Regarding claim 15, the claim recites similar subject matter as claim 1 and is rejected for the same reasons as stated above. Furthermore, McMackin teaches an analog to digital converter (140 in fig. 2A).
Regarding claim 16, the claim recites similar subject matter as claim 2 and is rejected for the same reasons as stated above.
Regarding claim 17, the claim recites similar subject matter as claim 3 and is rejected for the same reasons as stated above.
Regarding claim 18, the claim recites similar subject matter as claim 4 and is rejected for the same reasons as stated above.
Regarding claim 19, the claim recites similar subject matter as claims 5-6 and is rejected for the same reasons as stated above.
Claim(s) 7, 14, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pittaluga et al (US20220067457), McMackin et al (US20120038819) and Wu et al (US20220024415) in view of Chu et al ("Real-time privacy-preserving moving object detection in the cloud." Proceedings of the 21st ACM international conference on Multimedia. 2013, pages 597-600, retrieved from the Internet on 7/10/2026).
Regarding claim 7, the modified method of Pittaluga fails to teach a method wherein the machine learning process is trained to inverse-transform the distorted image and to identify individuals and objects in the inverse-transformed image.
However Chu teaches wherein the machine learning process is trained to inverse- transform the distorted image and to identify individuals and objects in the inverse-transformed image (pg. 599, section 2.4, wherein inverse transform operations on the encrypted image can be performed if motion activity is detected and an alarm is received).
Therefore taking the combined teachings of modified Pittaluga and Chu as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the steps of Chu into the method of modified Pittaluga. The motivation to combine Chu and modified Pittaluga would be to provide efficient encryption (section 5 of Chu).
Regarding claim 14, the claim recites similar subject matter as claim 7 and is rejected for the same reasons as stated above.
Regarding claim 20, the claim recites similar subject matter as claim 7 and is rejected for the same reasons as stated above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEON VIET Q NGUYEN whose telephone number is (571)270-1185. The examiner can normally be reached Mon-Fri 11AM-7PM.
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/LEON VIET Q NGUYEN/ Primary Examiner, Art Unit 2663
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