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 Filed Amendments/Remarks
Applicant’s filed amendments/remarks filed on 01/18/2024 have been entered.
Filed IDS of 01/18/2024 has been entered and considered.
Claims 1-7, and 10-20 have been amended.
Claim 21 has been cancelled.
Currently, claims 1-20 remained pending.
Please refer to the action below.
Examiner Notes
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. However, the claimed subject matter, not the specification, is the measure of the invention.
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 8, and 15 is/are rejected under 35 U.S.C. 102 (a)(1) as being unpatentable over Yonezawa et al. (JP 2020/078031, A1).
Regarding claim 1, Yonezawa teaches an information processing system (image information processing system 10 of at least Figs. 1-4 and 7) comprising: at least one memory 222 storing instructions, and
at least one processor 223 configured to execute the instructions to;
specify, in accordance with an analysis result based on a coded and distributed image, an image quality of an area including a specific part in the distributed image (a case exists in at least Figs. 3-4, 7 and the disclosure where the system sets and specify a specific ROI (dynamic ROI) 420/740 image quality value for inside and outside of the region in the distributed image in accordance with an analysis result at least Figs. 3-4 and the disclosure based on a coded and distributed image such as “even if the moving body is not detected thereafter, the image quality improvement processing is continued. Image quality improvement processing is performed during the time. That is, after it is determined that at least a part of the moving object region is included in the specific object ROI, the moving object is not detected from the specific object ROI, or it is determined that the moving object region is not included in the specific object ROI. Even in such a case, the image quality improving process is performed for a certain period of time. Here, the high image quality processing means encoding with higher image quality than other image areas (for example, quantization with a smaller quantization step and encoding). Since the duration of the image quality enhancement process may vary depending on the scene, the user may be allowed to set it. Alternatively, the control unit 223 may manage the history of past moving object detection and set the duration of the image quality enhancement process for each event. In step S570, the compression encoding unit 215 does not target the specific object ROI that does not include a part or all of the moving body region even if it is the specific object ROI, and the same inside and outside the specific object ROI. Encoding is set so that image quality is achieved. As an example, the compression encoding unit 215 sets a common qP value “43” inside and outside the specific object ROI for the selected frame image”); and
perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality (a case further exists in at least Figs. 3-4, 7 and the disclosure where the system sets up a uniform inside and outside quality image values in controlling in the said distributing image in which the image quality of the area 420 and/or 740 including the specific part is the specified image quality).
Regarding claim 8, Yonezawa teaches an information processing method (image information processing system 10 of at least Figs. 1-4 and 7 comprises said information processing method) comprising:
processing for specifying, in accordance with an analysis result based on a coded and distributed image, an image quality of an area including a specific part in the distributed image (a case exists in at least Figs. 3-4, 7 and the disclosure where the system sets and specify a specific ROI (dynamic ROI) 420/740 image quality value for inside and outside of the region in the distributed image in accordance with an analysis result at least Figs. 3-4 and the disclosure based on a coded and distributed image such as “even if the moving body is not detected thereafter, the image quality improvement processing is continued. Image quality improvement processing is performed during the time. That is, after it is determined that at least a part of the moving object region is included in the specific object ROI, the moving object is not detected from the specific object ROI, or it is determined that the moving object region is not included in the specific object ROI. Even in such a case, the image quality improving process is performed for a certain period of time. Here, the high image quality processing means encoding with higher image quality than other image areas (for example, quantization with a smaller quantization step and encoding). Since the duration of the image quality enhancement process may vary depending on the scene, the user may be allowed to set it. Alternatively, the control unit 223 may manage the history of past moving object detection and set the duration of the image quality enhancement process for each event. In step S570, the compression encoding unit 215 does not target the specific object ROI that does not include a part or all of the moving body region even if it is the specific object ROI, and the same inside and outside the specific object ROI. Encoding is set so that image quality is achieved. As an example, the compression encoding unit 215 sets a common qP value “43” inside and outside the specific object ROI for the selected frame image”); and
processing performing control for distributing the image in which the image quality of the area including the specific part is the specified image quality (a case further exists in at least Figs. 3-4, 7 and the disclosure where the system sets up a uniform inside and outside quality image values in controlling in the said distributing image in which the image quality of the area 420 and/or 740 including the specific part is the specified image quality).
Regarding claim 15, Yonezawa teaches an information processing apparatus 100 (image information processing system 10 of at least Figs. 1-4 and 7 comprises said information processing apparatus 100) comprising:
at least one memory 222 storing instructions, and
at least one processor 223 configured to execute the instructions to;
specify, in accordance with an analysis result based on a coded and distributed image, an image quality of an area including a specific part in the distributed image (a case exists in at least Figs. 3-4, 7 and the disclosure where the system sets and specify a specific ROI (dynamic ROI) 420/740 image quality value for inside and outside of the region in the distributed image in accordance with an analysis result at least Figs. 3-4 and the disclosure based on a coded and distributed image such as “even if the moving body is not detected thereafter, the image quality improvement processing is continued. Image quality improvement processing is performed during the time. That is, after it is determined that at least a part of the moving object region is included in the specific object ROI, the moving object is not detected from the specific object ROI, or it is determined that the moving object region is not included in the specific object ROI. Even in such a case, the image quality improving process is performed for a certain period of time. Here, the high image quality processing means encoding with higher image quality than other image areas (for example, quantization with a smaller quantization step and encoding). Since the duration of the image quality enhancement process may vary depending on the scene, the user may be allowed to set it. Alternatively, the control unit 223 may manage the history of past moving object detection and set the duration of the image quality enhancement process for each event. In step S570, the compression encoding unit 215 does not target the specific object ROI that does not include a part or all of the moving body region even if it is the specific object ROI, and the same inside and outside the specific object ROI. Encoding is set so that image quality is achieved. As an example, the compression encoding unit 215 sets a common qP value “43” inside and outside the specific object ROI for the selected frame image”); and
perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality (a case further exists in at least Figs. 3-4, 7 and the disclosure where the system sets up a uniform inside and outside quality image values in controlling in the said distributing image in which the image quality of the area 420 and/or 740 including the specific part is the specified image quality).
Claims 1-2, 4-5, 7-9, 11-12, 14-16, 18-19 is/are further rejected under 35 U.S.C. 102 (a)(1) as being unpatentable over YE et al. (CN 108780499, A1).
Regarding claim 1, YE teaches an information processing system 102 (image information processing device 102 at least Figs. 1-4 and the disclosure comprising a machine learning system trained to reconstruct encoded image data and to predict and specify an optimal quantization parameter (QP) based on a full reference image quality measurement of convolutional neural network (FRCNN) to at least distribute via a network the image to a display device 104, the QP as cited is “global (globally) distribution”) comprising:
at least one memory (memory 204 of at least Fig. 2), storing instructions, and
at least one processor 202 of Fig. 2 configured to execute the instructions to;
specify, in accordance with an analysis result based on a coded and distributed image, an image quality of an area including a specific part in the distributed image (a case exists in at least Figs. 3-4 and the disclosure where the system specify an image quality measure (such as FRCNN) and a quality threshold to determine the image block quality value as an area including a specific part in the distributed image, in accordance with at least a reconstruction image analysis block result 306 of the disclosure based on said coded and distributed image); and
perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality (a case further exists in the disclosure and Fig. 1-3 where the distribution of the image further comprises performed control for distributing the image in which the image quality of the area including the specific part is the specified image quality such as the optimal quality value sets for the region of interest is also sets as the specified image quality such as “video quality will not be on different image blocks and/or image frame. Further, the whole video quality can is optimized when the viewing user (such as user 110). According to the embodiment, the encoded video may be transmitted to one or more display devices via a communication network 106, such as the display device 104. In this case, the encoded video may be decoded and then presented at display device 104. The user 110 sensed during playback of the whole video quality can is highly optimized”).
Regarding claim 2 (according to claim 1), YE further teaches wherein the at least one processor is configured to specify the image quality in accordance with reliability of the analysis result (set optimal QP quantization parameter of the disclosure and Figs. 3-4 is specified as the image quality in accordance with at least a reliability threshold of an implied image reconstructing analysis result).
Regarding claim 4 (according to claim 1), YE further teaches wherein when the reliability of the analysis result is equal to or smaller than a threshold, the at least one processor is configured to
Regarding claim 5 (according to claim 1), YE further teaches wherein the at least one processor is configured to specify the image quality based on a bandwidth available in a network through which the image is distributed (specified QP of the disclosure is further set based on network bandwidth, bit rates and the like such as “QP is determined for coding such image block of the image block 302 bit number. Further, the QP control blocks (such as one or more reconstruction for image block 302 of the reconstructed image block 306a to 306n) of the visual quality. Generally, a smaller QP produced higher visual quality. However, this higher visual quality determined in this manner which may occur at a cost of higher bit rate. Ideally, the small QP can be used such as QP= "1" to realize the best visual quality. However, the bit rate may be limited by the external resources, such as limited by the bandwidth of the network (such as communication network 106). For a given rate, it is possible to properly distributing QP for each image block, so that video quality may be on different image block and the image frame of the video (such as video 108) consistent and so no fluctuation”).
Regarding claim 7 (according to claim 1), YE further teaches wherein the image quality includes an image quality based on at least one of a bit rate of coding, a frame rate of the coding, a quantization parameter of the coding, an area and a bit rate setting of each layer in hierarchical coding, and a setting of an image-capturing apparatus for capturing the image (specified QP of the disclosure is further set based on network bandwidth, bit rates and the like such as “QP is determined for coding such image block of the image block 302 bit number. Further, the QP control blocks (such as one or more reconstruction for image block 302 of the reconstructed image block 306a to 306n) of the visual quality. Generally, a smaller QP produced higher visual quality. However, this higher visual quality determined in this manner which may occur at a cost of higher bit rate. Ideally, the small QP can be used such as QP= "1" to realize the best visual quality. However, the bit rate may be limited by the external resources, such as limited by the bandwidth of the network (such as communication network 106). For a given rate, it is possible to properly distributing QP for each image block, so that video quality may be on different image block and the image frame of the video (such as video 108) consistent and so no fluctuation”).
Regarding claim 8, YE teaches an information processing method (image information processing device 102 at least Figs. 1-4 and the disclosure comprising said method and a machine learning system trained to reconstruct encoded image data and to predict and specify an optimal quantization parameter (QP) based on a full reference image quality measurement of convolutional neural network (FRCNN) to at least distribute via a network the image to a display device 104, the QP as cited is “global (globally) distribution”) comprising:
processing for specifying, in accordance with an analysis result based on a coded and distributed image, an image quality of an area including a specific part in the distributed image (a case exists in at least Figs. 3-4 and the disclosure where the system specify an image quality measure (such as FRCNN) and a quality threshold to determine the image block quality value as an area including a specific part in the distributed image, in accordance with at least a reconstruction image analysis block result 306 of the disclosure based on said coded and distributed image); and
processing performing control for distributing the image in which the image quality of the area including the specific part is the specified image quality (a case further exists in the disclosure and Fig. 1-3 where the distribution of the image further comprises performed control for distributing the image in which the image quality of the area including the specific part is the specified image quality such as the optimal quality value sets for the region of interest is also sets as the specified image quality such as “video quality will not be on different image blocks and/or image frame. Further, the whole video quality can is optimized when the viewing user (such as user 110). According to the embodiment, the encoded video may be transmitted to one or more display devices via a communication network 106, such as the display device 104. In this case, the encoded video may be decoded and then presented at display device 104. The user 110 sensed during playback of the whole video quality can is highly optimized”).
Regarding claim 9 (according to claim 8), YE further teaches wherein, in the specifying processing, the image quality is specified in accordance with reliability of the analysis result (set optimal QP quantization parameter of the disclosure and Figs. 3-4 is specified as the image quality in accordance with at least a reliability threshold of an implied image reconstructing analysis result).
Regarding claim 11 (according to claim 8), YE further teaches wherein in the specifying processing, when the reliability of the analysis result is equal to or smaller than a threshold, performs an analysis based on the image in the image quality (optimum QP value of further Figs. 3-4 and the disclosure is specified according to a set quality threshold when understoodly if said reliability of the analysis result is obviously equal to or smaller than a threshold, the at least one processor is configured to
Regarding claim 12 (according to claim 8), YE further teaches wherein in the specifying processing, the image quality is specified based on a bandwidth available in a network through which the image is distributed (specified QP of the disclosure is further set based on network bandwidth, bit rates and the like such as “QP is determined for coding such image block of the image block 302 bit number. Further, the QP control blocks (such as one or more reconstruction for image block 302 of the reconstructed image block 306a to 306n) of the visual quality. Generally, a smaller QP produced higher visual quality. However, this higher visual quality determined in this manner which may occur at a cost of higher bit rate. Ideally, the small QP can be used such as QP= "1" to realize the best visual quality. However, the bit rate may be limited by the external resources, such as limited by the bandwidth of the network (such as communication network 106). For a given rate, it is possible to properly distributing QP for each image block, so that video quality may be on different image block and the image frame of the video (such as video 108) consistent and so no fluctuation”).
Regarding claim 14 (according to claim 8), YE further teaches wherein the image quality includes an image quality based on at least one of a bit rate of coding, a frame rate of the coding, a quantization parameter of the coding, an area and a bit rate setting of each layer in hierarchical coding, and a setting of an image-capturing apparatus for capturing the image (specified QP of the disclosure is further set based on network bandwidth, bit rates and the like such as “QP is determined for coding such image block of the image block 302 bit number. Further, the QP control blocks (such as one or more reconstruction for image block 302 of the reconstructed image block 306a to 306n) of the visual quality. Generally, a smaller QP produced higher visual quality. However, this higher visual quality determined in this manner which may occur at a cost of higher bit rate. Ideally, the small QP can be used such as QP= "1" to realize the best visual quality. However, the bit rate may be limited by the external resources, such as limited by the bandwidth of the network (such as communication network 106). For a given rate, it is possible to properly distributing QP for each image block, so that video quality may be on different image block and the image frame of the video (such as video 108) consistent and so no fluctuation”).
Regarding claim 15, YE teaches an information processing apparatus 102 (image information processing device 102 at least Figs. 1-4 and the disclosure comprising said apparatus 102 and a machine learning system trained to reconstruct encoded image data and to predict and specify an optimal quantization parameter (QP) based on a full reference image quality measurement of convolutional neural network (FRCNN) to at least distribute via a network the image to a display device 104, the QP as cited is “global (globally) distribution”) comprising:
at least one memory (memory 204 of at least Fig. 2), storing instructions, and
at least one processor 202 of Fig. 2 configured to execute the instructions to;
specify, in accordance with an analysis result based on a coded and distributed image, an image quality of an area including a specific part in the distributed image (a case exists in at least Figs. 3-4 and the disclosure where the system specify an image quality measure (such as FRCNN) and a quality threshold to determine the image block quality value as an area including a specific part in the distributed image, in accordance with at least a reconstruction image analysis block result 306 of the disclosure based on said coded and distributed image); and
perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality (a case further exists in the disclosure and Fig. 1-3 where the distribution of the image further comprises performed control for distributing the image in which the image quality of the area including the specific part is the specified image quality such as the optimal quality value sets for the region of interest is also sets as the specified image quality such as “video quality will not be on different image blocks and/or image frame. Further, the whole video quality can is optimized when the viewing user (such as user 110). According to the embodiment, the encoded video may be transmitted to one or more display devices via a communication network 106, such as the display device 104. In this case, the encoded video may be decoded and then presented at display device 104. The user 110 sensed during playback of the whole video quality can is highly optimized”).
Regarding claim 16 (according to claim 15), YE further teaches wherein the at least one processor is configured to specify the image quality in accordance with reliability of the analysis result (set optimal QP quantization parameter of the disclosure and Figs. 3-4 is specified as the image quality in accordance with at least a reliability threshold of an implied image reconstructing analysis result).
Regarding claim 18 (according to claim 15), YE further teaches wherein when the reliability of the analysis result is equal to or smaller than a threshold, the at least one processor is configured to
Regarding claim 19 (according to claim 18), YE further teaches wherein the at least one processor is configured to specify the image quality based on a bandwidth available in a network through which the image is distributed (specified QP of the disclosure is further set based on network bandwidth, bit rates and the like such as “QP is determined for coding such image block of the image block 302 bit number. Further, the QP control blocks (such as one or more reconstruction for image block 302 of the reconstructed image block 306a to 306n) of the visual quality. Generally, a smaller QP produced higher visual quality. However, this higher visual quality determined in this manner which may occur at a cost of higher bit rate. Ideally, the small QP can be used such as QP= "1" to realize the best visual quality. However, the bit rate may be limited by the external resources, such as limited by the bandwidth of the network (such as communication network 106). For a given rate, it is possible to properly distributing QP for each image block, so that video quality may be on different image block and the image frame of the video (such as video 108) consistent and so no fluctuation”).
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 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.
Claims 6, 13, and 20 is/are rejected under 35 U.S.C. 103 as obvious over YE in view of Yonezawa.
Regarding claim 6 (according to claim 1), YE is silent regarding wherein the at least one processor is configured to improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part when the analysis based on the area of the specific part cannot be performed.
Yonezawa teaches a case of Figs. 3-4 a case “where a region of a specific object or a region of a moving object in a frame image is set as an ROI and the ROI is compression-encoded with a higher image quality than other image regions will be described” to obviously improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part. It would have been obvious to one of ordinary skill in the art at the time the invention was made to combine the teachings of YE in view of Yonezawa to include wherein said the at least one processor is configured to improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part when the analysis based on the area of the specific part cannot be performed, as discussed above, as YE in view of Yonezawa are in the same field of endeavor of identifying an image quality of an area and/or a specific part of a distributed image configured to improve the image quality of the a specific area of the specific part and perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality, Yonezawa’s architecture of improving image quality of the area of the specific part and degrades the image quality of an area other than the specific part complements the identifying image quality of the specific part of the distributed image and the performed control for distributing said image in which the image quality of the area including the specific part is the specified image quality of YE in the sense that when combined with the architecture of Yonezawa enabled the system obviously to specify a degraded image area, based on the image analysis an area of the specific part that cannot be detected, as an area of a lower quality value compared to the specify area region, as said degraded area understoodly in the art may be an area deemed of lower importance to the user so as capable of being distributed with a lower quality value whereby network resources and/or available bandwidth may be preserved, according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 13 (according to claim 1), YE is silent regarding wherein in the specifying processing, the image quality of the area of the specific part is improved and the image quality of an area other than the specific part is degraded when the analysis based on the area of the specific part cannot be performed.
Yonezawa teaches a case of Figs. 3-4 a case “where a region of a specific object or a region of a moving object in a frame image is set as an ROI and the ROI is compression-encoded with a higher image quality than other image regions will be described” to obviously improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part. It would have been obvious to one of ordinary skill in the art at the time the invention was made to combine the teachings of YE in view of Yonezawa to include wherein in the specifying processing, the image quality of the area of the specific part is improved and the image quality of an area other than the specific part is degraded when the analysis based on the area of the specific part cannot be performed, as discussed above, as YE in view of Yonezawa are in the same field of endeavor of identifying an image quality of an area and/or a specific part of a distributed image configured to improve the image quality of the a specific area of the specific part and perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality, Yonezawa’s architecture of improving image quality of the area of the specific part and degrades the image quality of an area other than the specific part complements the identifying image quality of the specific part of the distributed image and the performed control for distributing said image in which the image quality of the area including the specific part is the specified image quality of YE in the sense that when combined with the architecture of Yonezawa enabled the system obviously to specify a degraded image area, based on the image analysis an area of the specific part that cannot be detected, as an area of a lower quality value compared to the specify area region, as said degraded area understoodly in the art may be an area deemed of lower importance to the user so as capable of being distributed with a lower quality value whereby network resources and/or available bandwidth may be preserved, according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Regarding claim 20 (according to claim 15), YE is silent regarding wherein the at least one processor is configured to improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part when the analysis based on the area of the specific part cannot be performed.
Yonezawa teaches a case of Figs. 3-4 a case “where a region of a specific object or a region of a moving object in a frame image is set as an ROI and the ROI is compression-encoded with a higher image quality than other image regions will be described” to obviously improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part. It would have been obvious to one of ordinary skill in the art at the time the invention was made to combine the teachings of YE in view of Yonezawa to include wherein said processor is configured to improve the image quality of the area of the specific part and degrades the image quality of an area other than the specific part when the analysis based on the area of the specific part cannot be performed, as discussed above, as YE in view of Yonezawa are in the same field of endeavor of identifying an image quality of an area and/or a specific part of a distributed image configured to improve the image quality of the a specific area of the specific part and perform control for distributing the image in which the image quality of the area including the specific part is the specified image quality, Yonezawa’s architecture of improving image quality of the area of the specific part and degrades the image quality of an area other than the specific part complements the identifying image quality of the specific part of the distributed image and the performed control for distributing said image in which the image quality of the area including the specific part is the specified image quality of YE in the sense that when combined with the architecture of Yonezawa enabled the system obviously to specify a degraded image area, based on the image analysis an area of the specific part that cannot be detected, as an area of a lower quality value compared to the specify area region, as said degraded area understoodly in the art may be an area deemed of lower importance to the user so as capable of being distributed with a lower quality value whereby network resources and/or available bandwidth may be preserved, according to further known methods to yield predictable results since known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art as said combination is thus the adaptation of an old idea or invention using newer technology that is either commonly available and understood in the art thereby a variation on already known art (See MPEP 2143, KSR Exemplary Rationale F).
Claims Objections
Claims 3, 10, and 17 are not rejected over the prior arts of record, and 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. The prior arts do not specifically teach: [Claim 3] (Currently amended) The information processing system according to claim 1, wherein the at least one processor is configured to specify the image quality for the entire image when a subject cannot be detected based on the distributed image, the at least one processor is configured to specify the image quality of an area of the subject when the specific part of the subject cannot be detected based on the distributed image, and the at least one processor is configured to specify the image quality of the area of the specific part when an analysis based on the area of the specific part of the distributed image cannot be performed.
[Claim 10] (Currently amended) The information processing method according to claim 8, wherein in the specifying processing, the image quality is specified for the entire image when a subject cannot be detected based on the distributed image, the image quality is specified for the area of the subject when the specific part of the subject cannot be detected based on the distributed image, and the image quality is specified for the area of the specific part when an analysis based on the area of the specific part of the distributed image cannot be performed.
[Claim 17] (Currently amended) The information processing apparatus according to claim 15, wherein the at least one processor is configured to specify the image quality for the entire image when a subject cannot be detected based on the distributed image, the at least one processor is configured to specify the image quality of an area of the subject when the specific part of the subject cannot be detected based on the distributed image, and the at least one processor is configured to specify the image quality of the area of the specific part when an analysis based on the area of the specific part of the distributed image cannot be performed.
Conclusion
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/MARCELLUS J AUGUSTIN/Primary Examiner, Art Unit 2682 02/02/2026