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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 1/10/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
This application is a National Stage Entry of PCT/JP2022/030974 filed on August 16, 2022, the contents of all of which are incorporated herein by reference, in their entirety.
Response to Preliminary Amendment
A preliminary amendment filed on 1/10/2025 has been filed.
Claims 1-14, 19, and 20 have been amended.
Claims 1-20 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) an apparatus, a system, and a method, configured to recognizing a subject in the video. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 8, and 15 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Claim(s) 1, 8, and 15 are directed to an apparatus, method, i.e. process, i.e. a system.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The apparatus in claim 1 (system in claim8 and method in claim 15) comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding Claim(s) 1, 8, and 15: the method recites the steps (functions) of:
A video processing apparatus comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: (generic computer or components configured to perform a step)
generate image quality feature information indicating a feature of image quality information indicating an image quality of a video in time and space; (mental process including observation, evaluation, and data gathering and can be done mentally in the human mind)
generate integrated data obtained by integrating information regarding a video including a feature of the video in time and space and the image quality feature information; (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations)
and to execute recognition processing on a subject included in the video based on the integrated data. (mental process including observation, evaluation, and data gathering and can be done mentally in the human mind)
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). As such, a person could mentally analyze an image and determine a fill level, either mentally or using a pen and paper. The mere nominal recitation that the various steps are being executed by a device/in a device (e.g. processing unit) does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 8, and 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claim(s) 1, 8, and 15 do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer for “generating, indicating, obtaining, etc., as claimed in Claim(s) 1, 8, and 15 is a routine, well-understood and conventional process that is performed by computers.
Thus, since Claim(s) 1, 8, and 15 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1, 8, and 15 are not eligible subject matter under 35 U.S.C 101.
Regarding claims 2-7, 9-14, 16-20: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4, 6, 8-11, 13, 15-18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 9756323 B2) referred to as Yu hereinafter and further in view of Sugahara et al. (US 20190087976 A1) referred to as Sugahara hereinafter.
Regarding claim 1, Yu teaches A video processing apparatus comprising: (“Video quality assessment (VQA for short) plays a key role in the rapid development of video-related applications, which is commonly used in quality control of a wide variety of video services and performance comparison of various video processing algorithms.” Yu, col. 1, lines 20-24)
and at least one processor configured to execute the instructions to: generate image quality feature information indicating a feature of image quality information indicating an image quality of a video in time and space;
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Yu, col. 4, lines 19-33, Qframe is the claimed image quality feature.
generate integrated data obtained by integrating information regarding a video including a feature of the video in time and space and the image quality feature information;
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Yu, col. 4, lines 40-53, QLP is the claimed integrated data.
However, Yu does not teach at least one memory configured to store instructions; and to execute recognition processing on a subject included in the video based on the integrated data.
Sugahara teaches at least one memory configured to store instructions; (“In the model storage 43, the models that are learned for each shape of the objects that are gripped are saved. The model storage 43 could be volatile memory such as SRAM, DRAM or the like.” Sugahara, para. [0134])
and to execute recognition processing on a subject included in the video based on the integrated data. (“By using machine learning or deep learning, the image recognition models can be generated. Training images need to include multiple views of the object from different angles. Also, if the canned juice in cylindrical form and boxes also need to be gripped, image recognition models for other objects need to be generated.” Sugahara, para. [0039]), (“The three-dimensional imaging device 10, the image processing device 20 and the characteristic learning device 30 in FIG. 1 can be used to generate the aforementioned image recognition models for each object.” Sugahara, para. [0041]), and (“The robot 40 is a robot which grips the object and executes cargo handling tasks and assortment tasks. The robot 40 takes an image of the object with an image sensor. Then, based on the image recognition model generated by the characteristic learning device 30, the gripping location of the object is specified. The image recognition model includes a model that detects a certain object (object detection model) and a model that detects a region of an object (semantic segmentation model). First, by using the object detection model, the type of object is specified based on the shape which is indicated in the image. Then, by using the semantic segmentation model corresponding to the type of object, the coordinates of the gripping location is specified.” Sugahara, para. [0054])
Yu and Sugahara are combinable because they are from the same field of endeavor, image processing and pixel value corresponding to each frame.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Yu in light of Sugahara’s memory to store instruction and executing recognition processing on a subject included in the video based on the integrated data. One would have been motivated to do so because it can improve the quality of the three-dimensional model. (Sugahara, para. [0078])
Regarding claim 2, Yu in light of Sugahara teaches wherein the at least one processor is further configured to: generate the image quality feature information indicating a weight of pixel information in a frame of the video based on the image quality information, and generate a video in which weighting is performed in pixels of the frame of the video as the integrated data, based on the image quality feature information.
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Yu, col. 4, lines 19-35
Regarding claim 3, Yu in light of Sugahara teaches wherein the at least one processor is further configured to: generate the image quality feature information indicating a map of a feature amount of the image quality information in time and space, and generate the integrated data obtained by integrating the image quality feature information and video feature information that is information regarding the video and indicates a feature of the video in time and space. (“calculating a spatiotemporal domain local gradient similarity between each pixel point in each frame in the S.sub.r and a corresponding pixel point in a corresponding frame in the S.sub.d; marking the spatiotemporal domain local gradient similarity between a pixel point at a position of (x,y) in a number t frame in the S.sub.r and a pixel point at a position of (x,y) in a number t frame in the S.sub.d as G.sub.sim(x,y,t)” Yu, col. 3, lines 22-29)
Regarding claim 4, Yu in light of Sugahara teaches wherein the at least one processor is further configured to generate the video feature information based on the video. (“calculating a spatiotemporal domain local color similarity between each pixel point in each frame in the S.sub.r and the corresponding pixel point in the corresponding frame in the S.sub.d; marking the spatiotemporal domain local color similarity between the pixel point at the position of (x,y) in the number t frame in the S.sub.r and the pixel point at the position of (x,y) in the number t frame in the S.sub.d as C.sub.sim(x,y,t);” Yu, col. 3, lines 37-44)
Regarding claim 6, Yu in light of Sugahara teaches wherein the image quality information is information indicating a compression degree of a region of a frame included in the video. (“A LIVE video database and a CSIQ video database are used. Referring to the LIVE video database, there are 10 video segments without distortion; four distortion types are involved, which are MPEG-2 compression distortion, H.264 compression distortion, transmission distortion of bit-stream compressed with H.264 standard through IP network, and transmission distortion through wireless network; there are totally 150 segments of distorted videos which are all YUV420 format with a resolution of 768×432 and a length of 10 seconds; and two frame rates, 25 frames per second and 50 frames per second, are used. Referring to the CSIQ video database, there are 12 video segments without distortion; six distortion types are involved, which are motion JPEG compression distortion, H.264 compression distortion, HEVC compression distortion, wavelet compression distortion, loss distortion of wireless transmission, and additive white Gaussian noise distortion; there are totally 216 segments of distorted videos which are all YUV420 format with a resolution of 832×480 and a length of 10 seconds;” Yu, col. 8, lines 52-67, col. 9, lines 1-6)
Regarding claim 8, refer to the explanation of claim 1.
Regarding claim 9, refer to the explanation of claim 2.
Regarding claim 10, refer to the explanation of claim 3.
Regarding claim 11, refer to the explanation of claim 4.
Regarding claim 13, refer to the explanation of claim 6.
Regarding claim 15, refer to the explanation of claim 1.
Regarding claim 16, refer to the explanation of claim 2.
Regarding claim 17, refer to the explanation of claim 3.
Regarding claim 18, refer to the explanation of claim 4.
Regarding claim 20, refer to the explanation of claim 6.
Claim(s) 5, 7, 12, 14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Yu and Sugahara as mentioned above and further in view of Hashimoto (US 20220406036 A1).
Regarding claim 5, the combination of Yu and Sugahara does not teach wherein the video processing apparatus further includes a neural network trained such that a loss function calculated based on a recognition result of the recognition processing and a correct answer label of action recognition corresponding to a sample video to be sampled is equal to or less than a predetermined threshold, if the at least one processor acquires the sample video as the video.
Hashimoto teaches wherein the video processing apparatus further includes a neural network trained such that a loss function calculated based on a recognition result of the recognition processing and a correct answer label of action recognition corresponding to a sample video to be sampled is equal to or less than a predetermined threshold, if the at least one processor acquires the sample video as the video. (“the control unit 21 calculates an error between the output value obtained from the output layer 53 and the correct answer indicated by the correct answer data 32. The error (loss) may be calculated using a loss function.” Hashimoto, para. [0084]), (“the configuration of the correct answer data 32 is not limited in particular, and may be determined as appropriate depending on the embodiment, as long as the correct answer of the discrimination task can be specified so that the correct answer data 32 can be used in machine learning of at least one of the plurality of discriminators 5. For example, the correct answer data 32 may be constituted by information indicating whether or not each portion of the training data 31 includes a feature of that particular class. Alternatively, the correct answer data 32 may be constituted by information indicating the class of a feature included in each portion of the training data 31.” Hashimoto, para. [0077]), (“the control unit 21 may repeat adjustment of the values of the computation parameters of the discriminator 5 by the series of update processes until a predetermined condition such as executing a specified number of times or the sum of the calculated errors being a threshold value or less is satisfied.” Hashimoto, para. [0086]), and (“The training data 31C can be obtained by observing an examinee who drives a vehicle using the sensor SC or a sensor of the same type. The correct answer data 32C indicates the correct answer of a state discrimination task with respect to the training data 31C.” Hashimoto, para. [0129])
Yu, Sugahara, and Hashimoto are combinable because they are from the same field of endeavor, image processing in object identification.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Yu and Sugahara in light of Hashimoto’s correct answer label of action recognition corresponding to a sample video to be sampled is equal to or less than a predetermined threshold. One would have been motivated to do so because the accuracy of discriminating the class of a feature included in data can be improved. (Hashimoto, para. [0012])
Regarding claim 7, Hashimoto in view of Yu and Sugahara teaches wherein the at least one processor further recognizes an action of the subject. (“the sensing data obtained by the sensor SC is handled as object data and training data. The states and classes to be discriminated may be determined as appropriate depending on the embodiment. The states to be discriminated may include behavior of a driver” Hashimoto, para. [0128])
Regarding claim 12, refer to the explanation of claim 5.
Regarding claim 14, refer to the explanation of claim 7.
Regarding claim 19, refer to the explanation of claim 5.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PARDIS SOHRABY whose telephone number is (571)270-0809. The examiner can normally be reached Monday - Friday 9 am till 6pm.
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/PARDIS SOHRABY/Examiner, Art Unit 2664
/GANDHI THIRUGNANAM/Primary Examiner, Art Unit 2672
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