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 .
Response to Remark(s)
Applicant's amendment filed October 30th, 2025 has been fully entered and considered. Applicant’s amendment to the claims have overcome each and every objection, 112f and 112b rejection previously set forth in the Non-Final Office Action mailed on July 30th, 2025. Regarding the arguments to the previous prior art rejections and the 101 rejection, the examiner respectfully finds the arguments to be non-persuasive, see response to remarks section below. Accordingly, this action is made final.
Status of Claims
Claims 1-8 are pending, claims 1-7 have been amended, claim 8 has been added. Claims 1-8 remains rejected.
Response to Argument(s)
101 rejections:
In pages 7-19 of the remarks, the Applicants argue that the claims are 101 compliant, specifically discussing the independent claim 1 and claims 6-7. Wherein the Applicants centrally argue that the claim 1, evaluated with the support from the specification’s [0002-0010], indicates an integration into a practical application of having a technological improvement to the computer’s search functionality and enabling more accurate and robust search results. Importantly, the Applicants assert that the present application defines an unconventional and specific computer processing method that computes the “direction of change” of an object’s feature values contained in time-series frame images and uses this “direction of change” as search key which is an automation of a task that a human could perform mentally.
The Applicants further cited the English and Ex Parte Desjardins case to indicate that the present application share similar improvement and that the improvement in computer functionality should be found to be patent eligible under 35 USC 101.
The Applicants further touch on the requirement of step 2A Prong 1 analysis to read the claim based on BRI (broadest reasonable interpretation) to must be given in consistency with the specification that the BRI scope of broadest reasonable and not broadest possible, and that the scope must be carrying out these claim limitations together with the use of a computer and nothing in the specification suggest that any of the claim feature should be interpreted to mean anything occurring as a mental process.
The important points that the Applicants also focus on when indicating that the claimed features are more than processes practically performable in the human mind such as “detecting keypoints of an object from numerous frame images,” “computing a feature value for each keypoint as a multi-dimensional vector” further “computing direction in which those vectors change over time, and comparing this series of change patterns (e.g., increase[Wingdings font/0xE0]increase[Wingdings font/0xE0]maintain[Wingdings font/0xE0]decrease)” as a search key against a vast database of moving images; which are only achievable through computer technology exceeding the scope of human mental activity.
Regarding the mathematical concepts features within the claim, the Applicants argue that, even though, the claim involved mathematical concepts, the application are not direction to mathematical concepts.
Regarding the Step 2B of the pending rejection, the Applicants argue that, the additional elements should be analyzed as being combined to operate in an unconventional way, and not the critical inquiry I not whether each element is individually generic. Moreover, the entire process of the claim is more a mere aggregation of known elements, but as a whole, creates a new functionality that improves the search capability of the computer hence, considered “significantly more.”
Examiner’s reply:
The examiner respectfully disagrees with the Applicants’ arguments and find them to be incommensurate with the claim’s scope. Importantly, with the consideration of the Applicants’ assertion that the BRI scope of the claim should be in consistency with the specification, the examiner somewhat disagrees, as although the specification affiliates the understanding of the invention, however, the claim is construed based on BRI in light of the specification. That being said, the teachings of the specification cannot be imported to be the scope of the claim, claim’s BRI scope is determined solely based on claim’s language (see MPEP 2173.01 and 2111.01 for more details).
Therefore, with this important consideration, the examiner cannot agree and find them to be incommensurate with the BRI scope of the claim on the points that “an improvement to the computer’s search functionality and enabling more accurate and robust search results,” detecting keypoints of an object from numerous frame images,” “computing a feature value for each keypoint as a multi-dimensional vector” further “computing direction in which those vectors change over time, and comparing this series of change patterns (e.g., increase[Wingdings font/0xE0]increase[Wingdings font/0xE0]maintain[Wingdings font/0xE0]decrease)” as a search key against a vast database of moving images; there is no language in the claim, specifically the claim 1 being discussed, that suggest enabling accurate and robust search results,“ “…..using numerous frame images,” “…..multi-dimensional vector.,” etc., as mentioned.
The Applicants are further reminded that the requirement of Step 2A Prong 1 is that, the limitations of the claims are interpretable to be processes that a human mind can perform mentally with pen and paper, and that steps such as “detect a keypoint of an object…frame images,” “search for moving image by using the computer direction of change in the feature value as a key” to involve processes a human mind can perform, such as the human mind can observe images and detect keypoint, using certain given (already found or given as computed or numbers/values to be used based on) data/information here being the computed direction of change, to perform a search for a certain moving image; moreover, the steps of “computer a feature value…,” “compute a direction of change….” are all steps of explicitly computation mathematical operations.
The examiner also wants to bring to the Applicants’ attention that the last limitation “search for a moving image by using the computed direction of change in the feature value as a key” is in a language that, under BRI, does not reflect the idea of the Applicants’ argument, or the scope of the argument, importantly, “search for a moving image” can be interpreted to be searching for any images in a series of image (moving image) or a video, not necessarily indicating a searching for “search key against a vast database,” moreover the limitation simply recite “…as a key” without specifically referring to what “as a key”. Nevertheless, there is no recitation of anything specific being resulted as a search key.
On the argument bringing in of the case of English and Ex Parte Desjardins, the examiner finds them to be two different cases and not similar. The examiner prosecute on the basis of case-by-case and the claims of these two cases are different and that, nevertheless, the discussed English and Ex Parte Desjardins concerning with machine learning model trained with specific usage and training method that is different to the current application.
Regarding the Applicants’ argument on step 2B, the examiner finds the claim to recite the computer and computer components at mere recitation at high level of generality, no more than mere attempt to implement these discussed abstract ideas of mental processes and mathematical concepts using computer and its components. There is no recitation of an improvement, that with knowledge of one ordinary skill person in the art, would conclude that the claim 1 would creates a new functionality of a computer or improve the search capability of a computer to be considered “significantly more.” See the 101 rejection below for more details.
Therefore, the 101 rejection remains.
102 rejection:
In pages 19-21 of the remarks, the Applicants argue that the proposed Fotiadou does not teach or suggest the features of the claim 1 and claims 6-7:
“compute a feature value,” “compute a direction of change in the feature value, ” and “search for a moving image using the computed direction of change”
In support of the argument, the Applicants assert that even if Fotiadou may suggest that “frame in a sequence consists of the rotation angles of each joint,” however, does not suggest computing those rotation angles much less as the claimed “compute a direction of change in the feature value along a time axis of the firsts frame images in time series.”
Fotiadou, even if a rotation angle of a joint may be known from a frame among frames, such rotation angle does not imply a “change along a time axis” much less “alone a time axis of the first frame images in time series,” and that disclosed “rotation angle of a joint” is unknown to be the same or different in one frame as compared to another of any in sequence of images in time series. In other words, Fotiadou compare two entire motion sequences and creates a “correspondence matrix” to evaluate the similarity of poses between frames, Fotiadou does not suggest to extract or compute time-series change information, such as the claimed “direction of change” indicating how a feature value has changed overtime within a single query moving image, much less to also use that information as search key.
Examiner’s reply:
The examiner respectfully disagrees with the Applicants’ argument and find them to be incommensurate with the scope of the claim.
The Applicants are reminded that the claim is construed based on BRI in light of the specification. Therefore, regarding the argument that, asserted by the Applicants, the Fotiadou does not suggest to extract or compute time-series change information, such as the claimed “direction of change” indicating how a feature value has changed overtime within a single query moving image, much less to also use that information as search key, which the examiner finds to pertain to the last limitation of claim 1; the examiner finds to be incommensurate with the scope of the claim, the claim simply recite “search for a moving image by using the computed direction of change in the feature value as a key,” which, does not have any feature that equivalate “direction of change” to be indicating how a feature value has changed overtime, moreover, the claim simply mention “search for a moving image by using the computed direction of change” which can be understood to be searching for any series of image by using the computed direction of change, the word “by” does not strictly indicate that there is a strict criteria or requirement to search for the moving image. Moreover, the term “direction of change” is not a strict term that one ordinary skill person in the art would conclude that it strictly means indicating how a feature has changed overtime, therefore, by BRI, it is analogous to rotation angle of a joint as mapped in the rejection. Importantly, the term “as a key” does not refer to specifically what being recited to be “as a key,” nevertheless, “a key” can be analogous to anything that is the purpose of the processing and “a key” is not strictly, at all instances, indicating “a search key” as the term used in the Applicants’ argument.
Furthermore, regarding the other limitations of “compute a feature value,” “compute a direction of change in the feature value, ”; by BRI, the examiner finds the prior art to teach these features such as “compute a feature value” to be analogous to Fotiadou’s a value in the calculated matrix as disclosed in section 2, 1st par., bullet 1; and “compute a direction of change in the feature value” to be analogous to Fotiadou’s calculation of the rotation angles of the joints (rotation angles, an angle indicates a direction and rotation indicates a change, hence the term is analogous to direction of change), moreover, the rotation angle is calculated for the pose of the person and the pose is determined based on the calculate matrix, hence, the rotation angle is for the matrix of that pose, in other words, the direction of change if calculated for that feature value, in time-series since the image frames of concern/processing is in time-series (image sequence).
Therefore, the 102 rejections remains.
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 1-7 are rejected under 35 U.S.C. 101
Regarding Independent Claim 1 and its dependent claims 2-5, 8:
Step 1 Analysis: Claim 1 is directed to an apparatus/device, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 1 recites, in part, “detect a keypoint of an object included in each of the first frame images; compute a feature value of the detected keypoint for each of the first frame images; compute a direction of change in the feature value alone a time axis of the first frame images in time series; and search for a moving image by using the computed direction of change in the feature value as a key.” The limitations as mentioned, as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation which falls within the “Mental Processes” and “Mathematical Concept” groupings of abstract ideas. The limitations of:
“detect a keypoint of an object included in each of a plurality of the first frame images” is a step that a human can also perform mentally, based on BRI (broadest reasonable interpretation), through a process of observation and evaluation such as the human mind can observe images and detect keypoint of an object; “compute a feature value of the detected keypoint for each of the first frame images; compute a direction of change in the feature value alone a time axis of a plurality of the first frame images in time series” is a series of mathematical operations of computing a feature value based on certain given information/data and computing a direction of changes in the feature value based on a certain condition information/data hence, are just mathematical operations; “and search for a moving image by using the computed direction of change in the feature value as a key” is a step that a human can also perform mentally, based on BRI (broadest reasonable interpretation), through a process of observation and evaluation such as the human mind can observe certain already processed or given information/data and search for a moving image based on a certain criteria.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. particular, the claim recites the following additional element(s) –
At least one memory configured to store one or more instructions;
And at least one processor configured to execute the one or more instructions;
Acquire a plurality of first frame images in time series;
The additional elements – “…memory…store…instructions,” “…processor….execute…instructions” - recited at a high level of generality (i.e. as a memory storing instructions and processor executing instructions), and the limitation of “acquire….time series” is an insignificant extra-solution activity of data gathering of obtaining data/information. Such that these additional elements amount to no more than mere instructions to apply the exception. Accordingly, 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. The claim as a whole is directed to an abstract idea. Please see MPEP §2106.04.(d).III.C.
Step 2B Analysis: there are no additional elements that amount to significantly more than the judicial exception. Please see MPEP §2106.05. The claim is directed to an abstract idea.
For all of the foregoing reasons, claim 1 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 2-5 do not provide elements that overcome the deficiencies of the independent claim 1. Moreover, claim 2 recites, in part, “compute a magnitude of the change” is a mathematical operation of a computation following a formula of the change computation unit, as interpreted under 112f above, to be implemented by a generic additional element of a computer component; “search for a moving image by using the computed magnitude of the change as a key” includes an additional element of a generic computer component of the search unit to be recited at high level of generality to carry the structure of a processor, as interpreted under 112(f) section above, to perform a mental process abstract idea of searching step which the human mind can also perform through a process of observation and evaluation, under BRI. Claim 3 recites, in part, “compute a speed of the change” is a mathematical operation, “and search for a moving image by using the computed speed of the change as a key” is a step that the human mind can also perform through a mental process of observation and evaluation, by BRI, such as the human mind can observe certain information/data and search for a moving image. Claim 4 recites, in part, “search for a moving image by further using a representative image among a plurality of the first frame images as a key” is a mental process a human mind can perform, by BRI, through a process of observation and evaluation such as the human mind can observe certain information/data and search for a moving image, and further this abstract idea is recited to be implemented by an additional element recited at high level of generality of a well know processor executing function therefore, not an indication of a integration of the judicial exception into a practical application nor, being considered significantly more. Claim 5 recites, in part, “search for a moving image by using the feature value computed from the representative image” is a mental process a human mind can perform, by BRI, through a process of observation and evaluation such as the human mind can observe certain information/data and search for a moving image, and further this abstract idea is recited to be implemented by an additional element recited at high level of generality of a well know processor executing function therefore, not an indication of a integration of the judicial exception into a practical application nor, being considered significantly more. Claim 8 recites, in part, “in computing of the direction of change in the feature value, compute time-series data indicating a time-series change in the direction of change in the feature value by classifying a change in the feature value between the consecutive first frame images into one of a plurality of predetermined categories including at least a direction in which a numerical value increases and a direction in which the numerical value decreases” which gives further specification to the computation operation of the direction of change, wherein the computation includes further mathematical operations of computing time-series data a numerical values of certain condition, moreover, the step of classifying a change is a step which the human mind can perform mentally, hence, this limitation is a combination of steps of mathematical operations and mental processes; “in searching for the moving image, search for the moving image by using the time-series data as the key” is a step that a human can also perform mentally, based on BRI (broadest reasonable interpretation), through a process of observation and evaluation such as the human mind can observe certain already processed or given information/data and search for a moving image based on a certain criteria.
Accordingly, the dependent claims 2-5, 8 are not patent eligible under 101.
Regarding the independent claim 6, claim 6 recites analogous limitations to the independent claim 1 hence, can be analyzed under the same approach to be 101 rejected.
Regarding the independent claim 7, claim 7 recites analogous limitations to the independent claim 1 hence, can be analyzed under the same approach to be 101 rejected. Moreover, claim 7 recites further additional elements of a non-transitory storage medium storing a program causing a computer which are generic computer components performing generic functions hence, are not indicative of an integration of the judicial exceptions into a practical application, under Step 2A Prong 2, nor considered significantly more, under Step 2B. Therefore, claim 7 is not 101 eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 3-7 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Eftychia Fotiadou et. al. (“Activity-based methods for person recognition in motion capture sequences, Nov. 2014, Pattern Recognition Letters, Vol. 49, pp. 48-54” hereinafter as “Fotiadou”).
Regarding claim 1, Fotiadou discloses an image processing apparatus comprising: at least one memory configured to store one or more instructions; and at least one processor configured to execute the one or more instructions to (section 1, 2nd par., discloses the system for computer interaction hence, can be understood to include the use of a computer which includes a memory storing instructions to be executed by a processor for the invention): acquire a plurality of first frame images in time series (FIG. 1 illustrates a test sequence is being input into the system; moreover, these sequences include frames in time series [section 2.1, 1st par.]); detect a keypoint of an object included in each of the first frame images (FIG. 2 shows that the test sequence is being extracted features which can include features of a person such as disclosed in section I, 2nd par. [these features are analogous to keypoint of an object as claimed] for the frames of the test sequence); compute a feature value of the detected keypoint for each of the first frame images (section 2., 1st par., bullet 1, discloses constructing a correspondence matrix that describe which frame in the second sequence is similar to each frame of the first sequence, hence it indicates a value in the matrix for the comparison, this value can be understood to be analogous to the feature value as claimed by BRI); compute a direction of change in the feature value along a time axis of the first frame images in time series (section 2.1, 1st 2 paragraphs, discloses a calculation to determine the rotation angles of the join for the frame sequence to determine the pose of the person [rotation angle of the pose through the frames, indicates a direction of change, by BRI] of the frames being in time-series); and search for a moving image by using the computed direction of change in the feature value as a key (section 2., 1st par., bullet 2, discloses a calculating of similarity score is being performed to find the sequence similar to the test sequence based on the result of the correspondence matrix [as discussed earlier being the computed direction of change in the feature value] as a key [the similar sequence], by BRI, is analogous to the claimed limitation).
Regarding claim 3, Fotiadou discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to execute the one or more instructions to compute a speed of the change (section 6 discloses the additional feature can be used for the processing can include velocity which includes the computation of speed of the change as claimed), and search for a moving image by using the computed speed of the change as a key (therefore, when the additional feature being velocity, it can be understood the search for the moving image being similar to the input sequence is also based on the computed speed of the change as a key as claimed, by BRI).
Regarding claim 4, Fotiadou discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to execute the one or more instructions to search for a moving image by further using a representative image among a plurality of the first frame images as a key (FIG. 4 illustrates that the training sequences and the test sequence include images [any of which can be understood to be the representative image as claimed, by BRI] as a key [as the key for the searching as discussed above in claim 1]).
Regarding claim 5, Fotiadou discloses the image processing apparatus according to claim 4, wherein the at least one processor is further configured to execute the one or more instructions to search for a moving image by using the feature value computed from the representative image (as shown in FIG. 2, the feature value is being computed, as also discussed above in claim 1 above, from the frame of the sequences for the searching, by BRI, covers the scope of the claim).
Regarding claim 6, Fotiadou discloses an image processing method causing a computer to execute: (section 1, 2nd par., discloses the system for computer interaction hence, can be understood to include the use of a computer which includes a memory storing instructions to be executed by a processor for the invention): acquiring a plurality of first frame images in time series (FIG. 1 illustrates a test sequence is being input into the system; moreover, these sequences include frames in time series [section 2.1, 1st par.]); detecting a keypoint of an object included in each of the first frame images (FIG. 2 shows that the test sequence is being extracted features which can include features of a person such as disclosed in section I, 2nd par. [these features are analogous to keypoint of an object as claimed] for the frames of the test sequence); computing a feature value of the detected keypoint for each of the first frame images (section 2., 1st par., bullet 1, discloses constructing a correspondence matrix that describe which frame in the second sequence is similar to each frame of the first sequence, hence it indicates a value in the matrix for the comparison, this value can be understood to be analogous to the feature value as claimed by BRI); computing a direction of change in the feature value along a time axis of the first frame images in time series (section 2.1, 1st 2 paragraphs, discloses a calculation to determine the rotation angles of the join for the frame sequence to determine the pose of the person [rotation angle of the pose through the frames, indicates a direction of change, by BRI] of the frames being in time-series); and searching for a moving image by using the computed direction of change in the feature value as a key (section 2., 1st par., bullet 2, discloses a calculating of similarity score is being performed to find the sequence similar to the test sequence based on the result of the correspondence matrix [as discussed earlier being the computed direction of change in the feature value] as a key [the similar sequence], by BRI, is analogous to the claimed limitation).
Regarding claim 7, Fotiadou discloses a non-transitory storage medium storing a program causing a computer to: (section 1, 2nd par., discloses the system for computer interaction hence, can be understood to include the use of a computer which includes a non-transitory storage medium [RAM or ROM] storing instructions to be executed by a processor for the invention): acquire a plurality of first frame images in time series (FIG. 1 illustrates a test sequence is being input into the system; moreover, these sequences include frames in time series [section 2.1, 1st par.]); detect a keypoint of an object included in each of the first frame images (FIG. 2 shows that the test sequence is being extracted features which can include features of a person such as disclosed in section I, 2nd par. [these features are analogous to keypoint of an object as claimed] for the frames of the test sequence); compute a feature value of the detected keypoint for each of the first frame images (section 2., 1st par., bullet 1, discloses constructing a correspondence matrix that describe which frame in the second sequence is similar to each frame of the first sequence, hence it indicates a value in the matrix for the comparison, this value can be understood to be analogous to the feature value as claimed by BRI); compute a direction of change in the feature value along a time axis of the first frame images in time series (section 2.1, 1st 2 paragraphs, discloses a calculation to determine the rotation angles of the join for the frame sequence to determine the pose of the person [rotation angle of the pose through the frames, indicates a direction of change, by BRI] of the frames being in time-series); and search for a moving image by using the computed direction of change in the feature value as a key (section 2., 1st par., bullet 2, discloses a calculating of similarity score is being performed to find the sequence similar to the test sequence based on the result of the correspondence matrix [as discussed earlier being the computed direction of change in the feature value] as a key [the similar sequence], by BRI, is analogous to the claimed limitation).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Eftychia Fotiadou et. al. (“Activity-based methods for person recognition in motion capture sequences, Nov. 2014, Pattern Recognition Letters, Vol. 49, pp. 48-54” hereinafter as “Fotiadou”) in view of Xingyi Zhou et. al. (“Objects as Points, Apr. 2019, Computer Vision and Pattern Recognition” hereinafter as “Zhou”).
Regarding claim 2, Fotiadou discloses the image processing apparatus according to claim 1, wherein the at least one processor is further configured to execute the one or more instructions to (as discussed above in claim 1).
However, Fotiadou does not explicitly disclose computes a magnitude of the change, and search for a moving image by using the computed magnitude of the change as a key.
in the same field of pose estimation (abstract, Zhou), Zhou discloses compute a magnitude of the change (section 4 discloses equation, for the pose estimation, includes a calculation of the calculation of the absolute value of the difference between the two values [magnitude of the change as claimed, by BRI]), search for a moving image by using the computed magnitude of the change as a key (therefore, it can be understood the search is based on the finding of the absolute value of the difference between the two values as discussed previously, by BRI, it covers the scope of the claimed limitation; moreover, the processor that execute the instructions for the corresponding functions can be understood to be the change computation unit and the search unit as claimed).
Thus, it would have been obvious for a person of ordinary skill in the art before the effective filing date to modify Fotiadou to have a system that compute a magnitude of change and perform searching for a moving image by using the computed magnitude of the change as a key as taught by Zhou to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to use magnitude of change to perform pose estimation more efficiently (abstract and section 4, Zhou).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Eftychia Fotiadou et. al. (“Activity-based methods for person recognition in motion capture sequences, Nov. 2014, Pattern Recognition Letters, Vol. 49, pp. 48-54” hereinafter as “Fotiadou”) in view of Nida Khalid et. al. (“Modeling Two-Person Segmentation and Locomotion for Stereoscopic Action Identification: A Sustainable Video Surveillance System, Jan. 2021, Sustainability 2021, 13, 970” hereinafter as “Khalid”).
Regarding claim 8, Fotiadou discloses the image processing apparatus according to : The image processing apparatus according to wherein the first frame images are consecutive first frame images that are consecutive to each other (as discloses in section 2.1, 1st par., the 1st frame images as discussed above in claim 1, being denoted with X_s={x1, x2,….,xM} which includes consecutive frames), and wherein the at least one processor is further configured to execute the one or more instructions to: in computing of the direction of change in the feature value (as discussed above in claim 1), and in searching for the moving image, search for the moving image by using the time-series data as the key (as discussed above in claim 1, section 2., 1st par., bullet 2, discloses a calculating of similarity score is being performed to find the sequence similar to the test sequence based on the result of the correspondence matrix [as discussed earlier being the computed direction of change in the feature value] as a key [the similar sequence], by BRI, is analogous to the claimed limitation, as discussed above in claim 1, the similar sequence to be analogous to as a key, and the similar sequence is time-series data as recited in the claim).
However, Fotiadou does not explicitly disclose compute time-series data indicating a time-series change in the direction of change in the feature value by classifying a change in the feature value between the consecutive first frame images into one of a plurality of predetermined categories including at least a direction in which a numerical value increases and a direction in which the numerical value decreases.
In the same field of human action detection and pose estimation (abstract, Khalid) Khalid discloses compute time-series data indicating a time-series change in the direction of change in the feature value (section 3.2.2, 1st par., discloses determining direction of change alone each pixel for the position features, which includes pose angles [algorithm 2] which is analogous to the mapped rotation angle of Fotiadou to be analogous to the recited direction of change) by classifying a change in the feature value between the consecutive first frame images into one of a plurality of predetermined categories (basing on the determined directions of change to classify the change into human actions such as shown in table 7 to one of the categories as disclosed in section 3.2.2 and section 4.2) including at least a direction in which a numerical value increases and a direction in which the numerical value decreases (page 21, last par., discloses that the results in table 11 has number of MFs increases and decreases in the system’s recognition rate; therefore, there are numbers that increases and decreases; moreover, these numbers are representative of the result of the whole invention’s processing, hence, it is related to the directions of change in section 3.2.2, 1st 2 paragraphs, therefore, is analogous to at least a direction in which a number increases and a direction in which a number decreases, by BRI).
Thus, it would have been obvious for a person of ordinary skill in the art before the effective filing date to modify Fotiadou to perform computing of the direction of change in the feature value which includes computing time-series data indicating a time-series change in the direction of change in the feature value by classifying a change in the feature value between the consecutive first frame images into one of a plurality of predetermined categories including at least a direction in which a numerical value increases and a direction in which the numerical value decreases as taught by Khalid to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to perform human action recognition more accurately (abstract and section 3.2.2, Khalid).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHUONG HAU CAI whose telephone number is (571)272-9424. The examiner can normally be reached M-F 8:30 am - 5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chineyere Wills-Burns can be reached at (571) 272-9752. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PHUONG HAU CAI/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673