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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. 311419, filed on March 12, 2024, with the Israel Patent Office.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 2/12/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
The information disclosure statement (IDS) submitted on 6/20/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claims 1, 7, and 8 are objected to because of the following informalities: “identifying a region reflecting the object in the each frame” is recommended to be changed to “identifying a region reflecting the object in each frame”. Appropriate correction is required.
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 1-8 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) a computer-readable storage medium, a method, and a device, configured to identifying a region that reflects the object in the frame. 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, 7, and 8 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, 7, and 8 are directed to a method, i.e. process, a computer readable medium, i.e. a system, and a device.
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 computer readable medium in claim 1 (and device in claim 7 and method in claim 8) 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 claims 1, 7, and 8: the computer readable medium recites the steps (functions) of:
A computer-readable recording medium having stored therein a program for causing a computer to execute a process, the process comprising: (generic computer or components configured to perform a step)
performing segmentation to each frame of a series of frames reflecting an object, and thereby identifying a region reflecting the object in the each frame; (mental process including observation and evaluation, and can be done mentally in the human mind; analyzing image data)
for each pair of two chronologically contiguous frames among the series of frames, determining whether a first index value representing a degree of overlap between regions is at least equal to a first threshold value, the regions each being identified from a corresponding one of the pair of two chronologically contiguous frames; (mental process and mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations; determining numerical similarity and overlap relationships)
for each pair of two sequentially contiguous frames among the series of frames, determining whether a second index value representing a degree of similarity between the pair of two sequentially contiguous frames with respect to a specific type of feature is at least equal to a second threshold value; (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations; applying threshold-based rules)
identifying remaining frames obtained by excluding, from the series of frames, a number of sequentially contiguous frames anterior and posterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value, the number being inclusive of the pair; (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations; applying threshold-based rules)
and extracting, among the identified remaining frames, a first frame whose degree of similarity to a second frame with respect to the specific type of feature satisfies a specific condition. (mental process including observation and evaluation, and can be done mentally in the human mind; selecting or excluding frames based on those relationships)
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, 7, and 8 does/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, 7, and 8 do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer for "determining, identifying, and extracting, etc., as claimed in Claim(s) 1, 7, and 8 is a routine, well-understood and conventional process that is performed by computers.
Thus, since Claim(s) 1, 7, and 8 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, 7, and 8 are not eligible subject matter under 35 U.S.C 101.
Regarding claims 2-6: 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, 2, 4, 5, 7, and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Kwon et al. (US 20220066544 A1) referred to as Kwon hereinafter and further in view of Shimada (JP 2014123991 A).
Regarding claim 1, Kwon teaches A computer-readable recording medium having stored therein a program for causing a computer to execute a process, (“a non-transitory computer-readable medium is disclosed having instructions stored thereon, wherein execution of the instructions by a processor” Kwon, para. [0032]) the process comprising: performing segmentation to each frame of a series of frames reflecting an object, (“Human instance segmentation module 336 can directly detect occlusions between multiple people by utilizing human instance segmentation described in [115B] and parsing models [35B]. In an example, human instance segmentation module 336 aims at detecting all pixels in a video frame that belong to a person.” Kwon, para. [0088])
and thereby identifying a region reflecting the object in the each frame; (“a system is disclosed comprising an automated processing pipeline comprising a two-dimensional skeletal estimator configured to determine skeletal-associated points of a body of a person in a plurality of frames of a video data set;” Kwon, para. [0013], human points of body is the claimed object)
for each pair of two chronologically contiguous frames among the series of frames, determining whether a first index value representing a degree of overlap between regions is at least equal to a first threshold value, the regions each being identified from a corresponding one of the pair of two chronologically contiguous frames; (“for a gym exercise activity, 3D pose estimation calibration and filtering operation 328 detect outlier poses by interpolating and averaging the pose changes over 0.5-second sequences (considering the speed of the dumbbell exercise) with overlapping sliding windows at each timestep. The sliding window size can be selected to capture target activities without smoothing the motion excessively.” Kwon, para. [0108] and fig. 4B)
However, Kwon does not teach for each pair of two sequentially contiguous frames among the series of frames, determining whether a second index value representing a degree of similarity between the pair of two sequentially contiguous frames with respect to a specific type of feature is at least equal to a second threshold value; identifying remaining frames obtained by excluding, from the series of frames, a number of sequentially contiguous frames anterior and posterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value, the number being inclusive of the pair; and extracting, among the identified remaining frames, a first frame whose degree of similarity to a second frame with respect to the specific type of feature satisfies a specific condition.
Shimada teaches for each pair of two sequentially contiguous frames among the series of frames, determining whether a second index value representing a degree of similarity between the pair of two sequentially contiguous frames with respect to a specific type of feature is at least equal to a second threshold value; (“An acquisition unit that sequentially acquires frame images, and a first unit that determines whether the similarity between the first image region and the reference image in the one frame image acquired by the acquisition unit is equal to or greater than a first threshold value. The similarity between the reference image and the image of the second image region corresponding to the first image region in the frame image acquired before the one frame image is determined by the first determination unit; A second determination unit configured to determine whether or not the second threshold value is different from the second threshold value; and the second determination unit determines that the similarity is equal to or higher than the second threshold value.” Shimada, p. 10)
identifying remaining frames obtained by excluding, from the series of frames, a number of sequentially contiguous frames anterior and posterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value, the number being inclusive of the pair; (“An object detection method using an object detection device, wherein the step of sequentially acquiring frame images and the similarity between the first image region and the reference image in the acquired one frame image are equal to or greater than a first threshold value Determining whether or not there is a similarity between the reference image and the image of the second image region corresponding to the first image region in the frame image acquired before the one frame image, A step of determining whether or not the second threshold value is different from the first threshold value, and a determination that the similarity between the image in the second image region and the reference image is equal to or higher than the second threshold value.” Shimada, p. 10)
and extracting, among the identified remaining frames, a first frame whose degree of similarity to a second frame with respect to the specific type of feature satisfies a specific condition. (“That is, the similarity calculation unit 5b performs, for example, a face detection process, an edge detection process, a feature extraction process, etc. on each of the image data for live view display of each frame image F acquired sequentially by the image acquisition unit 5a. A plurality of image regions (detection candidate regions A) that are candidates for a specific subject image are extracted (see FIG. 3A).” Shimada, p. 3-4)
Kwon and Shimada are combinable because they are from the same field of endeavor, image processing in object detection.
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 Kwon in light of Shimada’s determining a second index after generating the first index of Kwon and using one or more of the indexes to determine which frames to exclude. One would have been motivated to do so because it can improve the detection accuracy for a specific object. (Shimada, abstract)
Regarding claim 2, Kwon in view of Shimada teaches the process further comprising forming a prototype-k-nearest neighbor (kNN), based on the region identified from the extracted first frame. (“Referring to FIG. 1A, the virtual IMU extraction system 102 can be used to train activity recognition classifier 122 using the generated virtual IMU data set 106. The output 106 of the virtual IMU extraction system 102 can be stored, e.g., in a storage area network (SAN) 124 to be accessed or distributed for the training of an activity recognition classifier 122. In other embodiments, the output 106 of the virtual IMU extraction system 102 can be used for analysis or visualization of IMU information of the human body. Activity recognition classifier 122 can include deep neural networks or other AI or machine learning systems such as convolutional neural networks (CNN), Long short-term memory (LSTM), random forest, decision tree, k-nearest neighbors (KNN), Support vector machines (SVM) described or referenced herein.” Kwon, para. [0075])
Regarding claim 4, Kwon in view of Shimada does not teach wherein the identifying includes excluding, from the series of frames, the number of sequentially contiguous frames that are from a prescribed number of frames anterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value, to a prescribed number of frames posterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value.
Shimada teaches wherein the identifying includes excluding, from the series of frames, the number of sequentially contiguous frames that are from a prescribed number of frames anterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value, to a prescribed number of frames posterior to the pair for which the first index is determined to be less than the first threshold value and/or for which the second index is determined to be less than the second threshold value. (“An acquisition unit that sequentially acquires frame images, and a first unit that determines whether the similarity between the first image region and the reference image in the one frame image acquired by the acquisition unit is equal to or greater than a first threshold value. The similarity between the reference image and the image of the second image region corresponding to the first image region in the frame image acquired before the one frame image is determined by the first determination unit; A second determination unit configured to determine whether or not the second threshold value is different from the second threshold value; and the second determination unit determines that the similarity is equal to or higher than the second threshold value.” Shimada, p. 10)
Regarding claim 5, Kwon in view of Shimada teaches wherein the first index value is based on intersection over union (IoU). (“An example tracking operation is the SORT tracking algorithm [7] that can track each person across the video sequence using a bipartite graph that can match with the edge weights as the intersection-over-union (IOU) distance between boundary boxes of people from consecutive frames.” Kwon, para. [0055])
Regarding claim 7, refer to the explanation of claim 1.
Regarding claim 8, refer to the explanation of claim 1.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Kwon and Shimada as mentioned above and further in view of Koji et al. (JP 2022036054 A) referred to as Koji hereinafter.
Regarding claim 3, the combination of Kwon and Shimada does not teach the process further comprising for each one of the identified remaining frames, calculating a sum of index values each representing a degree of similarity between the each one and other frames among the identified remaining frames with respect to the specific type of feature, wherein the extracting includes extracting a specific number of frames, starting from one having a smallest sum calculated, among the identified remaining frames.
Koji teaches the process further comprising for each one of the identified remaining frames, calculating a sum of index values each representing a degree of similarity between the each one and other frames among the identified remaining frames with respect to the specific type of feature, wherein the extracting includes extracting a specific number of frames, starting from one having a smallest sum calculated, among the identified remaining frames. (“A weight (bonding load) is set for each bond of each layer (51 to 53, 61 to 63). A threshold is set for each neuron, and basically, the output of each neuron is determined by whether or not the sum of the products of each input and each weight exceeds the threshold. The threshold value may be expressed by an activation function. In this case, the output of each neuron is determined by inputting the sum of the products of each input and each weight into the activation function and executing the operation of the activation function. The type of activation function may be arbitrarily selected. The weight of the connection between each neuron and the threshold value of each neuron included in each layer (51 to 53, 61 to 63) are examples of arithmetic parameters used in the arithmetic processing of each model (5, 6).” Koji, p. 6)
Kwon, Shimada, and Koji are combinable because they are from the same field of endeavor, image processing in object detection.
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 Kwon and Shimada in light of Koji’s sum of the index values. One would have been motivated to do so because it can improve the inspection accuracy. (Koji, p. 19)
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Kwon and Shimada as mentioned above and further in view of Katsuhisa (EP 2530931 A2).
Regarding claim 6, the combination of Kwon and Shimada does not teach wherein the second index value is based on scale invariant feature transform (SIFT).
Katsuhisa teaches wherein the second index value is based on scale invariant feature transform (SIFT). (“When a program is recorded in the recording device 15, the image feature quantity acquiring section 40 extracts and acquires image feature quantities of image frames in a prescribed interval decoded by the decoding processing section 14. Any of known methods such as a method for extracting and acquiring an image color histogram, a method for extracting and acquiring a SIFT (scale invariant feature transform) feature quantity, and a method for extracting and acquiring a HOG (histograms of oriented gradients) feature quantity may be employed as appropriate as the method for extracting and acquiring image feature quantities.” Katsuhisa, p. 6)
Kwon, Shimada, and Katsuhisa are combinable because they are from the same field of endeavor, image processing in object detection.
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 Kwon and Shimada in light of Katsuhisa’s SIFT. One would have been motivated to do so because it can improve user’s experience. (Katsuhisa, p. 9)
Conclusion
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/PARDIS SOHRABY/ Examiner, Art Unit 2664 /GANDHI THIRUGNANAM/Primary Examiner, Art Unit 2672
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