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 Amendment
Claims 1-6, 9-10 and 12-18 are currently amended. Claims 1-18 are pending.
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.
Claim(s) 1-2, 7-8 and 13-14 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Distributed and Efficient Object Detection via Interactions Among Devices, Edge, and Cloud to Guo et al., hereinafter, “Guo”.
Claim 1. Guo teaches A video processing system comprising: [Introduction] constantly capture the real-time pictures or videos of interested areas
an image quality control apparatus; [Fig. 2] End Device
and a detection apparatus, [Fig. 2] Edge Server
wherein the image quality control apparatus includes a first memory configured to store first instructions, [Fig. 2] End Device
and a first processor configured to execute the first instructions to; [Fig. 2] End Device, [VI. Conclusion] we propose an edge computing based object detection system and its implementation details for surveillance applications.
control image quality of each region of a video, [A. Image Compression for Object Detection] Compression ratio can be adjusted to accommodate the trade-off between storage size and image quality.
and transmit, to the detection apparatus, [Fig. 2] Edge Server the video of which the image quality is controlled, the detection apparatus includes a second memory configured to store second instructions, [VI. Conclusion] An RoI based image compression method is designed to compress the images for wireless transmission without significantly reducing the object detection accuracy.
and a second processor configured to execute the second instructions to; [Fig. 2] Edge Server, [VI. Conclusion] we propose an edge computing based object detection system and its implementation details for surveillance applications.
detect information regarding an object in the video transmitted from the image quality control apparatus, [Fig. 2] – object detection results
and notify the image quality control apparatus of the detected detection result, [Fig. 2], [IV. Edge Computing based Object Detection System] the ROI threshold in the End Device is updated.
and the first processor is further configured to execute the first instructions to determine the image quality of each region of the video to be controlled according to the detection result notified from the detection apparatus. [Fig. 2] and [A. RoI-Based Image Compression Method for Distributed Object Detection – entire section]
[B. RoI Compression and Detection, page 2910], [C. Detection results, page 2910] …the ROI is detected on the basis of the updated ROI threshold and compression is performed
Claim 2. Guo teaches wherein the second processor is further configured to execute the second instructions to detect an object in the video as the information regarding the object, [A. RoI-Based Image Compression Method for Distributed Object Detection, page 2906-2907] ROI threshold is updated based on the result of object detection in the video
and the first processor is further configured to execute the first instructions to determine the image quality of each region of the video to be controlled according to a detection result of the object. [C. Detection results, page 2910] Image quality is determined based on the ROI
Claim 7. Reviewed and analyzed in the same way as claim 1. See the above analysis and rationale.
Claim 8. Reviewed and analyzed in the same way as claim 2. See the above analysis and rationale.
Claim 13. Reviewed and analyzed in the same way as claim 1. See the above analysis and rationale.
Claim 14. Reviewed and analyzed in the same way as claim 2. See the above analysis and rationale.
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.
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.
Claim(s) 3-6, 9-12 and 15-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Distributed and Efficient Object Detection via Interactions Among Devices, Edge, and Cloud to Guo et al., hereinafter, “Guo” in view of JP 2019-140472 A to Ueda et al., hereinafter, “Ueda”.
Claim 3. Guo fails to explicitly teach determining the image quality of each region of the video to be controlled according to a recognition result of the action of the object. Ueda, in the field of analyzing image quality teaches wherein the second processor is further configured to execute the second instructions to recognize an action of an object in the video as the information regarding the object, [0037] The "attention moving target" is a target that is to move from the outside of the traveling road surface to the inside of the traveling road surface among the surrounding targets.
[0038] …it can be determined that the pedestrian m1 is the attention moving target. [-0041]
and the first processor is further configured to execute the first instructions to determine the image quality of each region of the video to be controlled according to a recognition result of the action of the object. [0040-0041]… To discriminate whether or not an object is a target. When the surrounding target is the attention moving target, the image compressing unit 114 proceeds to step S214, and sets the picture quality of the image region m1 including the pedestrian D4 who is the attention moving target to be higher than the picture quality of the image region m2 including the pedestrian D5 who is the surrounding target who is not the attention moving target.
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Guo with the teachings of Ueda [Problem to be Solved] to provide a technology capable of maintaining high image quality in a target area.
Claim 4. Guo fails to explicitly teach executing the first instructions to determine the image quality of each region of the video according to whether the information regarding the object is detected by the detection apparatus. Ueda, in the field of analyzing image quality teaches wherein the first processor is further configured to execute the first instructions to determine the image quality of each region of the video according to whether the information regarding the object is detected by the detection apparatus. [0030] In the image-quality setting process shown in FIG. 5, first, in step S200, the peripheral-target detecting unit 118 determines whether there is a peripheral target. When there is no surrounding target, the image quality setting process is ended… that the image quality setting processing may be performed for each of divided areas obtained by equally dividing the peripheral image. As a method of increasing the image quality, it is simplest to decrease the compression ratio. As another method, it is also possible to employ a method of averaging the pixel values of the pixels constituting the image region other than the image region T1 including the peripheral target D1 to reduce the resolutions. In addition, the picture quality may be improved by setting the image region T1 including the surrounding target D1 as a picture-in-picture region and setting the frame rate to be higher than that of a region other than the picture-in-picture region.
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Guo with the teachings of Ueda [Problem to be Solved] to provide a technology capable of maintaining high image quality in a target area.
Claim 5. Ueda further teaches wherein in a case where the information regarding the object is detected by the detection apparatus, the first processor is further configured to execute the first instructions to change an image quality of a region where the object is detected and an image quality of other regions. [0030]… … that the image quality setting processing may be performed for each of divided areas obtained by equally dividing the peripheral image…
Claim 6. Ueda further teaches wherein in a case where the information regarding the object is not detected by the detection apparatus, the first processor is further configured to execute the first instructions to maintain the image quality of each region of the video. [0030]… As another method, it is also possible to employ a method of averaging the pixel values of the pixels constituting the image region other than the image region T1 including the peripheral target D1 to reduce the resolutions. In addition, the picture quality may be improved by setting the image region T1 including the surrounding target D1 as a picture-in-picture region and setting the frame rate to be higher than that of a region other than the picture-in-picture region.
Claim 9. Reviewed and analyzed in the same way as claim 3. See the above analysis and rationale.
Claim 10. Reviewed and analyzed in the same way as claim 4. See the above analysis and rationale.
Claim 11. Reviewed and analyzed in the same way as claim 5. See the above analysis and rationale.
Claim 12. Reviewed and analyzed in the same way as claim 6. See the above analysis and rationale.
Claim 15. Reviewed and analyzed in the same way as claim 3. See the above analysis and rationale.
Claim 16. Reviewed and analyzed in the same way as claim 4. See the above analysis and rationale.
Claim 17. Reviewed and analyzed in the same way as claim 5. See the above analysis and rationale.
Claim 18. Reviewed and analyzed in the same way as claim 6. See the above analysis and rationale.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DELOMIA L GILLIARD whose telephone number is (571)272-1681. The examiner can normally be reached 8am-5pm.
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/DELOMIA L GILLIARD/Primary Examiner, Art Unit 2661
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