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 .
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 final rejection. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1/20/2026 has been entered.
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 1, 2, 6, 9-12, 15-16 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Leshniak, Itai (PGPUB Document No. 20220301127), hereafter referred as to “Leshniak”, in view of Jiang, Jiaorui et al (US Patent No. 11321010), hereafter, referred to as “Jiang”, in view of Yang, Yuanqing et al (PGPUB Document No. 20150189021 ), hereafter, referred to as “Yang”, in further view of Chen, Eric Hsuming et al (PGPUB Document No. 20180192058), hereafter, referred to as “Chen”.
Regarding Claim 1 (Currently Amended), Leshniak teaches A method for managing use of video data at a production assembly line to provide computer implemented services, the method comprising(Leshniak, Fig. 11 and para 0054 teach using image data for monitoring assembly line “a first image 1100 of an area around an assembly line, according to some embodiments. The first image 1100 may be recorded from a security or safety camera to monitor worker actions in the assembly line area”); obtaining by a video camera of a data originator at the production assembly line(Leshniak, para 0046 discloses obtaining video data from camera for processing “although the image 100 depicted in FIG. 5 shows automobiles in the region 506 at the intersection, this may not always be true for every image captured by the camera sensor during a live video stream”),
the reduced size first portion having at least one of a different color scale or a different resolution than the first portion of the video data(Leshniak, para 0029 downscaling the captured image “the post-processing circuit 208 may downscale the image. As described above, the overall size of the image may be the main cause of most processing bottlenecks. Therefore, some implementations may reduce the size of the image by downscaling the image”),
But Leshniak doesn’t explicitly teach a first portion of the video data; reducing, by the data originator, the first portion of the video data using a first reduction factor and a data reduction algorithm to obtain a reduced size first portion of data, the first reduction factor being based on: a first inference on assembly line production performance generated by the data originator using a second portion of the video data, a second inference on the assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference, the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable; generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference; and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network, the size reduced first portion of the video data to facilitate performance of a portion of the computer implemented services by the data user.
However, in the same field of endeavor data reduction by algorithm Jiang teaches a first portion of the video data; reducing, by the data originator, the first portion of the video data using a first reduction factor (Jiang, Fig.3 and col 6:65-67 through col 7: 1-5 disclose a portion of data is getting reduced “This portion of host data is labeled “reducing” 305 in FIG. 3. To the host, it appears that the reducing portion 305 is stored on managed drives 132. However, the storage system 100 processes the host data prior to actually storing the data on the managed drives 132 using one or more data reduction techniques, such as pattern detection, compression, and deduplication”; where col 7:48-51 further discloses that a reduction factor or rate is being used for data reduction “The data reduction rate, in some embodiments, is calculated as the amount of data stored by host…..”; where Leshniak in para 0046 discloses obtaining video data) and a data reduction algorithm to obtain a reduced size first portion of data(Jiang, col 7:19-23 further discloses reducing a portion of data by compression algorithm “Data can also be compressed 315, which can reduce the size of the data that is stored on managed drives 132. There are many compression algorithms, and the particular compression algorithm may be selected depending on the implementation” ), the first reduction factor being based on: a first inference on assembly line production performance generated by the data originator using a second portion of the video data(Jiang, col 7:51-55 further discloses that the first reduction factor is based on second/other portion of the data “The data reduction rate, in some embodiments, is calculated as the amount of data stored by host (reducing data 305+unreducible data 330+data reduction disabled 335) divided by the amount of storage space actually used to store that data on managed drives 132.”; where Leshniak in Fig. 11 and para 0054 teach using image data for monitoring assembly line),
the size reduced first portion of the video data to facilitate performance of a portion of the computer implemented services by the data user(Jiang, col 7:31-34 discloses data storing service is being facilitated by reducing storage space occupied by the data “the portion of effective capacity (TBe) that is classified as reducing, will see some savings from pattern detection 310, compression 315, and deduplication 320, such that the amount of usable capacity 305′ required to store the reducing data 305 is significantly lower than what the host considers to be stored on the storage system”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of reduction a portion of data of Jiang into capturing video data and reducing the video of Leshniak to produce an expected result of reducing the data for storing. The modification would be obvious because one of ordinary skill in the art would be motivated to reduce the size of the data for efficiently using storage capacity(Jiang, abstract).
But Leshniak and Jiang don’t explicitly teach a second inference on the assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference, the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable; generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference; and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network,
However, in the same field of endeavor of data reduction Yang teaches a second inference on the assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference(Yang, para 0074 discloses reduction evaluation of one portion of data is being determined by another portion’s reduction condition “In the case that the processing unit 12 determines that the second data amount reduction condition is satisfied, the processing unit 12 may perform a specific data amount reduction processing on the first information according to the second data amount reduction condition (for the sake of distinction, hereinafter referred to as the second data amount reduction processing)”; where Leshniak in Fig. 11 and para 0054 teach using image data for monitoring assembly line), the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable(Yang, para 0046 discloses reduction evaluation of data portion(second portion) is based on whether reduction degree as acceptable (for allowable bandwidth) “since in this case the bandwidth information indicates that the bandwidth of the communication link is relatively small, not sufficient to support smooth transmission of a large amount of data, in order to ensure transmission of the shared information, the second data amount reduction processing applied by the processing unit 12 may be a processing whose data amount reduction degree is relatively large. Herein, a data reduction degree of the second data amount reduction processing is greater than that of the first data amount reduction processing”); and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network(Yang, Fig. 2 and para 0074 discloses a communication network/link between user/display device and data processor “if the bandwidth information indicates that the bandwidth of the communication link is less than the second threshold value…..” ),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of evaluating data reduction degree for data transmission of Yang into data reduction processing of Leshniak and Jiang to produce an expected result of determining data reduction rate based on allowable data transmission criteria. The modification would be obvious because one of ordinary skill in the art would be motivated to transmit data based on network bandwidth to improve user experience(Yang, para 0004).
But Leshniak, Jiang and Yang don’t explicitly teach generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference;
However, in the same field of endeavor of data reduction Chen teaches generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference(Chen, claim 1 and 2 disclose applying/generating masked data for particular use such as where degradation of resolution is needed “wherein b) further comprises applying a mask to an edge of the one or more sections of the corresponding to the one or more regions of interest to generate a gradient of resolution degradation”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of making of data of Chen into data reduction processing of Leshniak, Jiang and Yang to produce an expected result of reducing the data size. The modification would be obvious because one of ordinary skill in the art would be motivated to transmit high compression data on network bandwidth to improve transmission load(Chen, claim 1).
Regarding claim 2 (Currently Amended), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 and Jiang further teaches wherein the data originator lacks capacity to process the first portion of the video data in a manner that is necessary for the computer-implemented services to be provided (Yang, para 0045 discloses that original data lacks reduction criteria at low bandwidth “if the bandwidth information indicates that the bandwidth of the communication link is less than or equal to the first threshold value and higher than a second threshold value (e.g., 500 Kbps to 1 Mbps), the processing unit 12 determines that the predetermined data amount reduction condition is satisfied (for the sake of distinction, hereinafter referred to as the first data amount reduction condition)”).
Regarding claim 6(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 and Yang further teaches wherein the data reduction algorithm reduces an amount of the video data to be provided using a variety of metrics(Yang, para 0009 discloses reduction process reduction rate or reduced amount of data is based on metrices such as network bandwidth and second or other portion’s reduction degree “a first data amount reduction processing is performed on the first information based on the first data amount reduction condition; or if the bandwidth information indicates that the bandwidth of the communication link is less than the second threshold value…… reduction processing is performed on the first information based on the second data amount reduction condition, and a data reduction degree of the second data amount reduction processing is greater than that of the first data amount reduction processing” ; where Leshniak in para 0046 discloses obtaining video data).
Regarding claim 7-8, Cancelled.
Regarding claim 9(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 6 and Jiang further teaches wherein the data reduction algorithm selectively excludes at least a portion of the first portion of the video data (Jiang, col 7:62-65 discloses reduction process selectively excluding duplicate data “if the pattern detection algorithms are used to detect patterns in the data, metadata is generated correlating tracks of data with the recognized patterns. Similarly, metadata is used in connection with deduplication to identify aspects of the data stored on the storage volume that have been removed prior to storage” ; where Leshniak in para 0046 discloses obtaining video data ).
Regarding claim 10(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 9 and Yang further teaches wherein the portion of the first portion of the data comprises a continuous portion of a scene depicted in the first portion of the video data (Yang, para 0061 discloses reduction process of on continuous data depicting scenes (video data) “Performing data amount reduction processing on the first information (video data) of the first user as acquired in real-time at the first electronic device side” ; Leshniak in para 0046 discloses obtaining video data).
Regarding claim 11(Original), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 10 and Yang further teaches wherein the portion of a scene is selected using an optimization process (Yang, para 0054 discloses optimizing scene (video frames) by data reduction process “ the processing unit 12 may further perform data amount reduction processing on the first information by selecting a portion of representative video frames in the first information ” ).
Regarding claim 12(Currently Amended), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 and Yang further teaches wherein the evaluation criteria provides a framework for weighing different factors that contribute to identifying reduction factors usable to reduce the second portion of the video data, the different factors comprising a factor from a list of factors consisting of(Yang, para 0074 discloses reduction evaluation is considering/weighing of one portion of data is being determined by another portion’s reduction condition “In the case that the processing unit 12 determines that the second data amount reduction condition is satisfied, the processing unit 12 may perform a specific data amount reduction processing on the first information according to the second data amount reduction condition (for the sake of distinction, hereinafter referred to as the second data amount reduction processing)” ; where Leshniak in para 0046 discloses obtaining video data):
computational resources used for generating the first inference and the second inference(Yang, para 0044 further discloses available bandwidth resource inference on data reduction amount is determined “if the bandwidth information indicates that the bandwidth of the communication link is less than or equal to the first threshold value and higher than a second threshold value (e.g., 500 Kbps to 1 Mbps), the processing unit 12 determines that the predetermined data amount reduction condition is satisfied……….In the case that the processing unit 12 determines that the first data amount reduction condition is satisfied, the processing unit 12 may perform data amount reduction processing on the first information based on the first data amount reduction condition” );
accuracy of the first inference and the second inference; and computational resources used to transmit the second portion of the video data (Yang, para 0019 discloses consideration of threshold values (accuracies) for determining data reduction amount “if the bandwidth information indicates that the bandwidth of the communication link is less than or equal to the first threshold value and higher than a second threshold value, then the processing unit determines that the predetermined data amount reduction condition is satisfied” )
Jiang teaches and the size reduced second portion of the video data (Jiang, col 11:49-52 discloses depending on the desired size of the data to be stored reductio ratio can be increased “increasing the data reduction ratio on data stored in the storage system 100 to increase effective storage capacity” ).
Regarding Claim 15 (Currently Amended), Leshniak teaches A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations(Leshniak, Fig. 14 discloses a system with processor, memory and storages for executing computing instructions) for managing use of video data at a production assembly line to provide computer implemented services, the operations comprising(Leshniak, Fig. 11 and para 0054 teach using image data for monitoring assembly line “a first image 1100 of an area around an assembly line, according to some embodiments. The first image 1100 may be recorded from a security or safety camera to monitor worker actions in the assembly line area”): obtaining, by a video camera of a data originator at the production assembly line(Leshniak, para 0046 discloses obtaining video data from camera for processing “although the image 100 depicted in FIG. 5 shows automobiles in the region 506 at the intersection, this may not always be true for every image captured by the camera sensor during a live video stream”), the reduced size first portion having at least one of a different color scale or a different resolution than the first portion of the video data(Leshniak, para 0029 downscaling the captured image “the post-processing circuit 208 may downscale the image. As described above, the overall size of the image may be the main cause of most processing bottlenecks. Therefore, some implementations may reduce the size of the image by downscaling the image”),
But Leshniak doesn’t explicitly teach a first portion of the video data; reducing, by the data originator, the first portion of the video data using a first reduction factor and a data reduction algorithm to obtain a reduced size first portion of data, the first reduction factor being based on: a first inference on assembly line production performance generated by the data originator using a second portion of the video data, a second inference assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference, the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable; generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference; and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network, the size reduced first portion of the video data to facilitate performance of a portion of the computer implemented services by the data user.
However, in the same field of endeavor data reduction by algorithm Jiang teaches a first portion of the video data; reducing, by the data originator, the first portion of the video data using a first reduction factor (Jiang, Fig.3 and col 6:65-67 through col 7: 1-5 disclose a portion of data is getting reduced “This portion of host data is labeled “reducing” 305 in FIG. 3. To the host, it appears that the reducing portion 305 is stored on managed drives 132. However, the storage system 100 processes the host data prior to actually storing the data on the managed drives 132 using one or more data reduction techniques, such as pattern detection, compression, and deduplication”; where col 7:48-51 further discloses that a reduction factor or rate is being used for data reduction “The data reduction rate, in some embodiments, is calculated as the amount of data stored by host…..”; where Leshniak in para 0046 discloses obtaining video data) and a data reduction algorithm to obtain a reduced size first portion of data(Jiang, col 7:19-23 further discloses reducing a portion of data by compression algorithm “Data can also be compressed 315, which can reduce the size of the data that is stored on managed drives 132. There are many compression algorithms, and the particular compression algorithm may be selected depending on the implementation” ), the first reduction factor being based on: a first inference on assembly line production performance generated by the data originator using a second portion of the video data(Jiang, col 7:51-55 further discloses that the first reduction factor is based on second/other portion of the data “The data reduction rate, in some embodiments, is calculated as the amount of data stored by host (reducing data 305+unreducible data 330+data reduction disabled 335) divided by the amount of storage space actually used to store that data on managed drives 132.”; where Leshniak in Fig. 11 and para 0054 teach using image data for monitoring assembly line ),
the size reduced first portion of the video data to facilitate performance of a portion of the computer implemented services by the data user(Jiang, col 7:31-34 discloses data storing service is being facilitated by reducing storage space occupied by the data “the portion of effective capacity (TBe) that is classified as reducing, will see some savings from pattern detection 310, compression 315, and deduplication 320, such that the amount of usable capacity 305′ required to store the reducing data 305 is significantly lower than what the host considers to be stored on the storage system”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of reduction a portion of data of Jiang into capturing video data and reducing the video of Leshniak to produce an expected result of reducing the data for storing. The modification would be obvious because one of ordinary skill in the art would be motivated to reduce the size of the data for efficiently using storage capacity(Jiang, abstract).
But Leshniak and Jiang don’t explicitly teach a second inference assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference, the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable; generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference; and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network,
However, in the same field of endeavor of data reduction Yang teaches a second inference assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference(Yang, para 0074 discloses reduction evaluation of one portion of data is being determined by another portion’s reduction condition “In the case that the processing unit 12 determines that the second data amount reduction condition is satisfied, the processing unit 12 may perform a specific data amount reduction processing on the first information according to the second data amount reduction condition (for the sake of distinction, hereinafter referred to as the second data amount reduction processing)”; where Leshniak in Fig. 11 and para 0054 teach using image data for monitoring assembly line), the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable(Yang, para 0046 discloses reduction evaluation of data portion(second portion) is based on whether reduction degree as acceptable (for allowable bandwidth) “since in this case the bandwidth information indicates that the bandwidth of the communication link is relatively small, not sufficient to support smooth transmission of a large amount of data, in order to ensure transmission of the shared information, the second data amount reduction processing applied by the processing unit 12 may be a processing whose data amount reduction degree is relatively large. Herein, a data reduction degree of the second data amount reduction processing is greater than that of the first data amount reduction processing”); and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network(Yang, Fig. 2 and para 0074 discloses a communication network/link between user/display device and data processor “if the bandwidth information indicates that the bandwidth of the communication link is less than the second threshold value…..” ),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of evaluating data reduction degree for data transmission of Yang into data reduction processing of Leshniak and Jiang to produce an expected result of determining data reduction rate based on allowable data transmission criteria. The modification would be obvious because one of ordinary skill in the art would be motivated to transmit data based on network bandwidth to improve user experience(Yang, para 0004).
But Leshniak, Jiang and Yang don’t explicitly teach generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference;
However, in the same field of endeavor of data reduction Chen teaches generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference (Chen, claim 1 and 2 disclose applying/generating masked data for particular use such as where degradation of resolution is needed “wherein b) further comprises applying a mask to an edge of the one or more sections of the corresponding to the one or more regions of interest to generate a gradient of resolution degradation”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of making of data of Chen into data reduction processing of Leshniak, Jiang and Yang to produce an expected result of reducing the data size. The modification would be obvious because one of ordinary skill in the art would be motivated to transmit high compression data on network bandwidth to improve transmission load(Chen, claim 1).
Regarding claim 16 (Currently Amended), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 15 and Jiang further teaches wherein the data originator lacks capacity to process the first portion of the video data in a manner that is necessary for the computer-implemented services to be provided (Yang, para 0045 discloses that original data lacks reduction criteria at low bandwidth “if the bandwidth information indicates that the bandwidth of the communication link is less than or equal to the first threshold value and higher than a second threshold value (e.g., 500 Kbps to 1 Mbps), the processing unit 12 determines that the predetermined data amount reduction condition is satisfied (for the sake of distinction, hereinafter referred to as the first data amount reduction condition)”).
Regarding Claim 18 (Currently Amended), Leshniak teaches A data processing system, comprising: a processor; and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing user interactions between a user and at least one user device, the operations comprising(Leshniak, Fig. 14 discloses a system with processor, memory and storages for executing computing instructions): obtaining, by a video camera of a data originator, a first portion of video data at a production assembly line(Leshniak, para 0046 discloses obtaining video data from camera for processing “although the image 100 depicted in FIG. 5 shows automobiles in the region 506 at the intersection, this may not always be true for every image captured by the camera sensor during a live video stream”);
the reduced size first portion having at least one of a different color scale or a different resolution than the first portion of the video data(Leshniak, para 0029 downscaling the captured image “the post-processing circuit 208 may downscale the image. As described above, the overall size of the image may be the main cause of most processing bottlenecks. Therefore, some implementations may reduce the size of the image by downscaling the image”),
But Leshniak doesn’t explicitly teach reducing, by the data originator, the first portion of the video data using a first reduction factor and a data reduction algorithm to obtain a reduced size first portion of data, the first reduction factor being based on: a first inference on assembly line production performance generated by the data originator using a second portion of the video data, a second inference on assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference, the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable; generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference; and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network, the size reduced first portion of the video data to facilitate performance of a portion of the computer implemented services by the data user.
However, in the same field of endeavor data reduction by algorithm Jiang teaches reducing, by the data originator, the first portion of the video data using a first reduction factor (Jiang, Fig.3 and col 6:65-67 through col 7: 1-5 disclose a portion of data is getting reduced “This portion of host data is labeled “reducing” 305 in FIG. 3. To the host, it appears that the reducing portion 305 is stored on managed drives 132. However, the storage system 100 processes the host data prior to actually storing the data on the managed drives 132 using one or more data reduction techniques, such as pattern detection, compression, and deduplication”; where col 7:48-51 further discloses that a reduction factor or rate is being used for data reduction “The data reduction rate, in some embodiments, is calculated as the amount of data stored by host…..”; where Leshniak in para 0046 discloses obtaining video data) and a data reduction algorithm to obtain a reduced size first portion of data(Jiang, col 7:19-23 further discloses reducing a portion of data by compression algorithm “Data can also be compressed 315, which can reduce the size of the data that is stored on managed drives 132. There are many compression algorithms, and the particular compression algorithm may be selected depending on the implementation” ), the first reduction factor being based on: a first inference on assembly line production performance generated by the data originator using a second portion of the video data(Jiang, col 7:51-55 further discloses that the first reduction factor is based on second/other portion of the data “The data reduction rate, in some embodiments, is calculated as the amount of data stored by host (reducing data 305+unreducible data 330+data reduction disabled 335) divided by the amount of storage space actually used to store that data on managed drives 132.”; where Leshniak in Fig. 11 and para 0054 teach using image data for monitoring assembly line),
the size reduced first portion of the video data to facilitate performance of a portion of the computer implemented services by the data user(Jiang, col 7:31-34 discloses data storing service is being facilitated by reducing storage space occupied by the data “the portion of effective capacity (TBe) that is classified as reducing, will see some savings from pattern detection 310, compression 315, and deduplication 320, such that the amount of usable capacity 305′ required to store the reducing data 305 is significantly lower than what the host considers to be stored on the storage system”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of reduction a portion of data of Jiang into capturing video data and reducing the video of Leshniak to produce an expected result of reducing the data for storing. The modification would be obvious because one of ordinary skill in the art would be motivated to reduce the size of the data for efficiently using storage capacity(Jiang, abstract).
But Leshniak and Jiang don’t explicitly teach a second inference assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference, the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable; generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference; and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network,
However, in the same field of endeavor of data reduction Yang teaches a second inference on assembly line production performance generated by the data originator using a size reduced second portion of the video data, and evaluation criteria for the first inference and the second inference (Yang, para 0074 discloses reduction evaluation of one portion of data is being determined by another portion’s reduction condition “In the case that the processing unit 12 determines that the second data amount reduction condition is satisfied, the processing unit 12 may perform a specific data amount reduction processing on the first information according to the second data amount reduction condition (for the sake of distinction, hereinafter referred to as the second data amount reduction processing)”; where Leshniak in Fig. 11 and para 0054 teach using image data for monitoring assembly line), the evaluation criteria being usable to identify whether a second reduction factor used to obtain the size reduced second portion of the video data is acceptable (Yang, para 0046 discloses reduction evaluation of data portion(second portion) is based on whether reduction degree as acceptable (for allowable bandwidth) “since in this case the bandwidth information indicates that the bandwidth of the communication link is relatively small, not sufficient to support smooth transmission of a large amount of data, in order to ensure transmission of the shared information, the second data amount reduction processing applied by the processing unit 12 may be a processing whose data amount reduction degree is relatively large. Herein, a data reduction degree of the second data amount reduction processing is greater than that of the first data amount reduction processing” ; where Leshniak in para 0046 discloses obtaining video data); and providing, by the data originator and to a data user that is remote to the data originator and operably connected via a network(Yang, Fig. 2 and para 0074 discloses a communication network/link between user/display device and data processor “if the bandwidth information indicates that the bandwidth of the communication link is less than the second threshold value…..” ),
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of evaluating data reduction degree for data transmission of Yang into data reduction processing of Leshniak and Jiang to produce an expected result of determining data reduction rate based on allowable data transmission criteria. The modification would be obvious because one of ordinary skill in the art would be motivated to transmit data based on network bandwidth to improve user experience(Yang, para 0004).
But Leshniak, Jiang and Yang don’t explicitly teach generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference;
However, in the same field of endeavor of data reduction Chen teaches generating derived data by masking at least one of the first inference or the second inference; providing the derived data to an entity not generating the first inference or the second inference (Chen, claim 1 and 2 disclose applying/generating masked data for particular use such as where degradation of resolution is needed “wherein b) further comprises applying a mask to an edge of the one or more sections of the corresponding to the one or more regions of interest to generate a gradient of resolution degradation”);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of making of data of Chen into data reduction processing of Leshniak, Jiang and Yang to produce an expected result of reducing the data size. The modification would be obvious because one of ordinary skill in the art would be motivated to transmit high compression data on network bandwidth to improve transmission load(Chen, claim 1).
Regarding claim 19 (Currently Amended), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 18 and Jiang further teaches wherein the data originator lacks capacity to process the first portion of the video data in a manner that is necessary for the computer-implemented services to be provided(Yang, para 0045 discloses that original data lacks reduction criteria at low bandwidth “if the bandwidth information indicates that the bandwidth of the communication link is less than or equal to the first threshold value and higher than a second threshold value (e.g., 500 Kbps to 1 Mbps), the processing unit 12 determines that the predetermined data amount reduction condition is satisfied (for the sake of distinction, hereinafter referred to as the first data amount reduction condition)”; where Leshniak, para 0046 discloses obtaining video data from camera).
Claim 3, 14, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Leshniak, Itai (PGPUB Document No. 20220301127), hereafter referred as to “Leshniak”, in view of Jiang, Jiaorui et al (US Patent No. 11321010), hereafter, referred to as “Jiang”, in view of Yang, Yuanqing et al (PGPUB Document No. 20150189021 ), hereafter, referred to as “Yang”, in further view of Chen, Eric Hsuming et al (PGPUB Document No. 20180192058), hereafter, referred to as “Chen”, in further view of Ribeiro, Claudio et al (PGPUB Document No. 20190356885), hereafter, referred to as “Ribeiro”.
Regarding claim 3 (Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 but don’t explicitly teach wherein the first portion of the data and the second portion of the data are generated by the data originator at different points in time, the first portion of the data being generated after the second portion of the video data.
However, in the same field of endeavor of data stream Ribeiro teaches wherein the first portion of the data and the second portion of the data are generated by the data originator at different points in time, the first portion of the data being generated after the second portion of the video data(Ribeiro, para 0190 discloses that data streams are being generated at different time “the processor 1410 analyzes each video stream separately and may use metadata within the video streams to time-synchronize the streams. The metadata for each video data stream may include a time-and-date stamp, which permits the processor 1410 to align the video frames of the video data streams even though such streams may be received at different times by the video processing apparatus 1406”; where McClure in para 0115 discloses obtaining video data).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of obtaining data streams from multiple sources of Ribeiro into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of considering data from multiple sources which generated at different times. The modification would be obvious because one of ordinary skill in the art would be motivated to analyze data in real time(Ribeiro, para 0111).
Regarding claim 14(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 but don’t explicitly teach wherein the data user uses the data obtained from multiple data originators to process the video data.
However, in the same field of endeavor of data reduction Yang teaches wherein the data user uses the data obtained from multiple data originators to process the video data(Ribeiro, para 0190 discloses that data streams having different origination are being processed “the video processing apparatus 1406 receives video data streams from multiple sources (e.g., cameras 101-104), the processor 1410 analyzes each video stream separately and may use metadata within the video streams to time-synchronize the streams” ; where McClure in para 0115 discloses obtaining video data).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of obtaining data streams from multiple sources of Ribeiro into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of considering data from multiple sources which generated at different times. The modification would be obvious because one of ordinary skill in the art would be motivated to analyze data in real time(Ribeiro, para 0111).
Regarding claim 17(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 15 but don’t explicitly teach wherein the first portion of the data and the second portion of the data are generated by the data originator at different points in time, the first portion of the data being generated after the second portion of the video data.
However, in the same field of endeavor of data stream Ribeiro teaches wherein the first portion of the video data and the second portion of the video data are generated by the data originator at different points in time, the first portion of the video data being generated after the second portion of the video data (Ribeiro, para 0190 discloses that data streams are being generated at different time “the processor 1410 analyzes each video stream separately and may use metadata within the video streams to time-synchronize the streams. The metadata for each video data stream may include a time-and-date stamp, which permits the processor 1410 to align the video frames of the video data streams even though such streams may be received at different times by the video processing apparatus 1406” ; where McClure in para 0115 discloses obtaining video data).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of obtaining data streams from multiple sources of Ribeiro into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of considering data from multiple sources which generated at different times. The modification would be obvious because one of ordinary skill in the art would be motivated to analyze data in real time(Ribeiro, para 0111).
Regarding claim 20(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 18 but don’t explicitly teach wherein the first portion of the data and the second portion of the video data are generated by the data originator at different points in time, the first portion of the data being generated after the second portion of the video data.
However, in the same field of endeavor of data stream Ribeiro teaches wherein the first portion of the video data and the second portion of the data are generated by the data originator at different points in time, the first portion of the data being generated after the second portion of the video data (Ribeiro, para 0190 discloses that data streams are being generated at different time “the processor 1410 analyzes each video stream separately and may use metadata within the video streams to time-synchronize the streams. The metadata for each video data stream may include a time-and-date stamp, which permits the processor 1410 to align the video frames of the video data streams even though such streams may be received at different times by the video processing apparatus 1406” ; where McClure in para 0115 discloses obtaining video data).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of obtaining data streams from multiple sources of Ribeiro into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of considering data from multiple sources which generated at different times. The modification would be obvious because one of ordinary skill in the art would be motivated to analyze data in real time(Ribeiro, para 0111).
Claim 4-5 and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Leshniak, Itai (PGPUB Document No. 20220301127), hereafter referred as to “Leshniak”, in view of Jiang, Jiaorui et al (US Patent No. 11321010), hereafter, referred to as “Jiang”, in view of Yang, Yuanqing et al (PGPUB Document No. 20150189021 ), hereafter, referred to as “Yang”, in view of Chen, Eric Hsuming et al (PGPUB Document No. 20180192058), hereafter, referred to as “Chen”, in further view of Yamamoto, Akira et al (PGPUB Document No. 20230021108), hereafter, referred to as “Yamamoto”.
Regarding claim 4(Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 but don’t explicitly teach wherein reducing the first portion of the data comprises: identifying a type of data of the first portion of the data; selecting the data reduction algorithm from a repository based on the identified type of data; generating a configured data reduction algorithm using: the selected data reduction algorithm, and the first reduction factor; and processing the first portion of the data using the configured data reduction algorithm to obtain the reduced size first portion of data.
However, in the same field of endeavor of data reduction Yamamoto teaches wherein reducing the first portion of the data comprises: identifying a type of data of the first portion of the data; selecting the data reduction algorithm from a repository based on the identified type of data(Yamamoto, para 0134 teaches determining compression/reduction algorithm based on data/media type “the compression algorithm suitable for the media type can be determined, and thus the data reduction rate can be further increased”); generating a configured data reduction algorithm using: the selected data reduction algorithm, and the first reduction factor; and processing the first portion of the data using the configured data reduction algorithm to obtain the reduced size first portion of data(Yamamoto, para 0133 teaches determining compression/reduction algorithm based on data/media type which has different compression factor/rate to reduce data (first portion of data) “the processor determines different compression algorithms for moving image data, still image data, and audio data. In addition, in a case where the moving image data, the still image data, and the audio data are uncompressed data….. the processor determines a compression algorithm with the highest compression rate from among compression algorithms that satisfy a compression speed of 100 MB/s for each of a moving image, a still image, and an audio. As such, the compression algorithm with an average compression speed may be determined”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of selecting data reduction algorithm based on data type of Yamamoto into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of reducing data based on their types. The modification would be obvious because one of ordinary skill in the art would be motivated to select data reduction algorithm to optimize compression rete in respect to compression speed(Yamamoto, para 0004-0005).
Regarding claim 5(Original), Leshniak, Jiang, Yang, Chen and Yamamoto teach all the limitations of claim 4 and Yamamoto further teaches wherein the repository comprises different data reduction algorithms associated with different types of data(Yamamoto, para 0134 teaches determining compression/reduction algorithm based on data/media type “the compression algorithm suitable for the media type can be determined, and thus the data reduction rate can be further increased”), and at least two of the different data reduction algorithms being adapted to selectively add portions of a source data to a reduced size source data based on different schemas, and the different schemas being unable to be used on other types of the different types of data from those of the different types of data associated with each of the at least two of the different data reduction algorithms(Yamamoto, para 0046 teaches selection of two different reduction algorithm “In the present invention, a compression algorithm having a compression rate higher than that of the compression algorithm initially applied is applied later to improve the data reduction rate”).
Regarding claim 21 (Previously Presented), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 18 but don’t explicitly teach wherein reducing the first portion of the video data comprises: identifying a type of video data of the first portion of the video data; selecting the data reduction algorithm from a repository based on the identified type of data; generating a configured data reduction algorithm using: the selected data reduction algorithm, and the first reduction factor; and processing the first portion of the video data using the configured data reduction algorithm to obtain the reduced size first portion of data.
However, in the same field of endeavor of data reduction Yamamoto teaches wherein reducing the first portion of the video data comprises: identifying a type of video data of the first portion of the video data; selecting the data reduction algorithm from a repository based on the identified type of data(Yamamoto, para 0134 teaches determining compression/reduction algorithm based on data/media type “the compression algorithm suitable for the media type can be determined, and thus the data reduction rate can be further increased”); generating a configured data reduction algorithm using: the selected data reduction algorithm, and the first reduction factor; and processing the first portion of the video data using the configured data reduction algorithm to obtain the reduced size first portion of data(Yamamoto, para 0133 teaches determining compression/reduction algorithm based on data/media type which has different compression factor/rate to reduce data (first portion of data) “the processor determines different compression algorithms for moving image data, still image data, and audio data. In addition, in a case where the moving image data, the still image data, and the audio data are uncompressed data….. the processor determines a compression algorithm with the highest compression rate from among compression algorithms that satisfy a compression speed of 100 MB/s for each of a moving image, a still image, and an audio. As such, the compression algorithm with an average compression speed may be determined”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of selecting data reduction algorithm based on data type of Yamamoto into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of reducing data based on their types. The modification would be obvious because one of ordinary skill in the art would be motivated to select data reduction algorithm to optimize compression rete in respect to compression speed(Yamamoto, para 0004-0005).
Regarding claim 22 (Previously Presented), Leshniak, Jiang, Yang, Chen and Yamamoto teach all the limitations of claim 21 and Yamamoto further teaches wherein the repository comprises different data reduction algorithms associated with different types of data(Yamamoto, para 0134 teaches determining compression/reduction algorithm based on data/media type “the compression algorithm suitable for the media type can be determined, and thus the data reduction rate can be further increased”), and at least two of the different data reduction algorithms being adapted to selectively add portions of a source data to a reduced size source data based on different schemas, and the different schemas being unable to be used on other types of the different types of data from those of the different types of data associated with each of the at least two of the different data reduction algorithms(Yamamoto, para 0046 teaches selection of two different reduction algorithm “In the present invention, a compression algorithm having a compression rate higher than that of the compression algorithm initially applied is applied later to improve the data reduction rate”).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Leshniak, Itai (PGPUB Document No. 20220301127), hereafter referred as to “Leshniak”, in view of Jiang, Jiaorui et al (US Patent No. 11321010), hereafter, referred to as “Jiang”, in view of Yang, Yuanqing et al (PGPUB Document No. 20150189021 ), hereafter, referred to as “Yang”, in view of Chen, Eric Hsuming et al (PGPUB Document No. 20180192058), hereafter, referred to as “Chen”, in further view of Ying, Zhiwei et al (PGPUB Document No. 20150043653), hereafter, referred to as “Ying”.
Regarding claim 13 (Original), Leshniak, Jiang, Yang and Chen teach all the limitations of claim 1 but don’t explicitly teach wherein the evaluation criteria defines a threshold for a difference between the first inference and the second inference, the evaluation criteria indicating that the second reduction factor is unacceptable when the difference between the first inference and the second inference exceeds the threshold.
However, in the same field of endeavor of data reduction Ying teaches wherein the evaluation criteria defines a threshold for a difference between the first inference and the second inference, the evaluation criteria indicating that the second reduction factor is unacceptable when the difference between the first inference and the second inference exceeds the threshold (Ying, para 0034 discloses a compression/data reduction criteria based threshold of degree of difference in compression “where primary type of compression is a version of MPEG, the degree of difference may also be compared to a second higher threshold of degree of difference. While the results of the comparison to the first threshold may determine whether the primary or secondary type of compression is used”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of selecting data reduction algorithm based on data type of Ying into data reduction processing of Leshniak, Jiang, Yang and Chen to produce an expected result of reducing data based on motion in video. The modification would be obvious because one of ordinary skill in the art would be motivated to select different types of data reduction/compression process based on motion in videos to optimize resource consumption(Ying, para 0015).
Response to Arguments
I. 35 U.S.C §103
Applicant’s arguments filed on 1/20/2026 have been fully considered but are
moot because the independent claim 1, 15 and 18 have been amended with newly added features which applicant’s arguments are directed towards. Since claims have been amended with new features, a new ground of rejection is presented.
Conclusion
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/ABDULLAH A DAUD/Examiner, Art Unit 2164 /AMY NG/Supervisory Patent Examiner, Art Unit 2164
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