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 Amendment
The Amendment filed 01/16/2026 in response to the Non-Final Office Action mailed 10/16/2025 has been entered.
Claims 21-38 are currently pending in U.S. Patent Application No. 18/510,354 and an Office action on the merits follows.
Subject Matter Eligibility under 35 USC § 101
Applicant’s remarks filed 01/16/2026 regarding eligibility analysis have been considered and determined non-persuasive. Reference may be made to that analysis/rationale as provided in the Interview Summary mailed 1/27/2026, conducted after and in response to Applicant’s remarks filed 1/16/2026. The claims as amended remain recited at a high level of generality failing to preclude interpretation drawing e.g. “performing shot detection” and “identify[ing] an activity associated with the video segment” (and providing a corresponding activity label) under the mental processes grouping, even in view of that broad use of deep learning architecture failing to serve for integration at Prong Two in view of the ‘apply it’ considerations of MPEP 2106.05(f). Such a finding/analysis is consistent with the most recent Examples provided in the 2024 PEG, in addition to both the August and December 2025 Memos.
Response to 35 USC § 112 Rejections
In view of the foregoing amendments and Applicant’s supporting remarks, claim rejections under 35 U.S.C. § 112(b) are withdrawn. Applicant’s remarks suggest Examiner’s rejection of “instructions” (apparatus claim(s) 28/35), as having no inherent and therefore definite structure, erroneously mistakes breadth for indefiniteness. Remarks are further understood to assert that at least “machine readable instructions” as amended, if not “instructions” more broadly, would be recognized by POSITA as necessarily structural in nature (in the context of claims directed to a system/apparatus), much the way instructions recited for a non-transitory CRM claim do not typically give rise to questions regarding structural definiteness. Examiner finds this argument persuasive, and notes that even Google’s Batch Normalization patent (US 10,417,562 B2) features claims directed to a system comprising instructions as structural elements. Corresponding rejections to the claims are withdrawn accordingly.
Response to Double Patenting Rejections
Applicant’s remarks at page 11 traverse Double Patenting rejections without specifying any manner in which the foregoing amendments may serve to distinguish the claimed invention, in a non-obvious manner, from those claims of reference previously identified. Remarks request effectively holding in abeyance such rejections until agreement on the scope of allowable claims enables evaluation of the same. While this seems an advantageous use of time to the Examiner, the Examiner is obligated to present early, and maintain where applicable, all pertinent grounds of rejection and avoid any piecemeal Examination. See e.g. MPEP 2173.06 and 707.07(g). See also MPEP 1205.02 regarding how any request to hold rejections in abeyance (in the context of Appeal Brief Content) may not meet the requirements of 37 CFR 41.37(c)(1)(iv). Examiner maintains that obvious modification to claims of reference warrants those concise Double Patenting rejection(s) reproduced below.
Response to 35 USC § 102/103 Rejections
Applicant's 01/16/2026 arguments asserting the proposed combination of Ji et al. (US
2011/0182469 A1) in view of Chang et al. (US 2017/0238055 A1), and Ji more specifically, fail(s) to fairly disclose/suggest “perform shot detection on a video to detect shot boundaries based on content changes in the video” (for independent claim(s) 21/28/35 as amended), have been fully considered and determined non-persuasive. Ji’s selection of a fixed number (5-7) of frames (facilitating input into 3D-CNN 24) for each cube 22 evaluated by CNN 24 in response to detected changes in content (e.g. human presence vs. absence and/or start vs stop of track as part of hypothesis generation 10) is not disqualifying for that/those reason(s) presented in the Interview Summary mailed 1/22/2026. The amended claim language places no constraints on the length of the shot in terms of frames (understandably so), and/or how many frames may be included pre and/or post the detected change/‘current frame’. The claim minimally requires the shot (grouping of frames) be determined based on the detected change broadly, which is a requirement met in Ji’s hypothesis generation 10 in view of Ji’s human detection 12 and tracking 14 disclosure. Ji as applied does not require a “shot” to correspond only to a single multi-frame cube instance (to any assertion in Applicant’s remarks that the shot of Ji is always fixed in size and in no way dynamic/variable/on the basis of the human track). Instead Ji is applicable in view of a shot corresponding to one or more of a plurality of multi-frame cubes 22. Ji is still concerned with considering primarily those frames pertinent to the human track as part of hypothesis generation 10, prior to and for the classification and ‘post-processing’ steps (20 and 30 respectively). Stated differently, as understood by the Examiner Ji’s human detection and tracking would be superfluous if the entire video/sequence of frames (to include even those portions that do not concern a human track) was supplied in 7 frame increments, to 3D-CNN 24. Examiner also understands the state of the art to be such that shot detection on the basis of content changes broadly (as an element considered individually) is common/not novel (in the context of video summarization). Furthermore, permissible interpretation of ‘content changes’ under a plain meaning need not involve more than a change that is e.g. the presence/absence of a human and/or the start/stop of a related track. Examiner maintains that references of record as reasonably combined serve to teach/suggest the instant claims as amended.
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.
Claim(s) 21-38 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, in particular an Abstract Idea – determining/providing a label for a video segment, an associated confidence/probability of correct classification, and one or more indications of an associated object (e.g. bounding box) – falling under at least the (c) mental processes grouping (concepts performable in the human mind including an observation, evaluation, judgement, opinion), not ‘integrated into a practical application’ at Prong Two of Step 2A and without ‘significantly more’ at Step 2B.
Step 1: The claim(s) in question are directed to a computer implemented method for classifying a video segment activity. (Step 1: Yes). As an additional note regarding Step 1 analysis, “memory” is understood to exclude transitory signal embodiments. Applicant’s Specification at [0098] discloses transitory signals within a ‘medium’, and also ‘non-transitory medium’ embodiments in e.g. [0046], however a ‘memory’ in the context of an apparatus is understood to exclude transitory signal embodiments.
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. Representative/independent claim(s) 21/28/35 recite(s) – “perform shot detection on a video to … extract a video segment”, “identify an activity associated with the video segment”, and “provid[ing] a label for the video segment, the label to identify an activity associated with the video segment”, and for claim 35 “detect[ing] an object in the video segment”, individually and collectively falling under the (c) mental processes grouping (concepts performable in the human mind including an observation, evaluation, judgement, opinion). As is made clear in the July 17, 2024 PEG (available for Applicant’s reference at: https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf ), the fact that these steps are recited as being performed with/by one or more processor circuits and/or based on ‘utilizing’ a ‘deep learning architecture’ broadly (even a CNN comparable to the ANN of the recent PEG) (MPEP 2106.05(f)), does not serve to preclude the limitations in question from also being drawn to the mental processes grouping. Considerations similar to those identified in the 101 analysis as presented in the Final Rejection mailed 03/09/2023 for parent application 17/201,969 and Interview Summary 06/16/2023, remain pertinent/applicable – and more so in view of similar/supporting analysis of the 2024 PEG (see Example 47 claim 2 steps (d)-(f)). See also MPEP 2106.04(a)(2) describing how the use of a ‘computer as a tool’ and/or pen and paper as physical aids may still fall under the mental processes grouping. Dependent claims are similarly analyzed for Prong One purposes as they inherit at least those limitations identified above. (Step 2A, Prong One: Yes).
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (1) identifying whether there are any ‘additional elements’ recited in the claim beyond the judicial exception, and (2) evaluating those ‘additional elements’ individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d). Examiner notes for consideration at Prong Two of 2A that MPEP 2106.05(a), (b), (c), and (e) generally concern elements that may be indicative of integration, whereas 2106.05(f), (g), and (h) generally concern elements that are not likely indicative of integration. As an additional note, ‘additional elements’ are generally limitations excluded from interpretation under the Abstract Idea groupings, and may comprise portions of limitations otherwise identified as falling under those Abstract Idea groupings of the 2019 PEG (e.g. any ‘determination’ that may be made mentally accompanied by the use of a neural network and/or generic computer hardware considered under the ‘apply it’ considerations of 2106.05(f) – as identified above in the Prong One analysis). Any ‘providing’/outputting broadly, and ‘collection’ of data (i.e. image/video acquisition(s), etc.,), be they images for training any learning model and/or data/images visually observable/ evaluated by a user/operator, also fail(s) to integrate at least in view of MPEP 2106.05(g) (extra-solution data gathering/output) and/or 2106.05(h) as ‘generally linking’ the exception to a field of use involving machine learning. Examiner also pre-emptively notes with respect to 2106.05(a), that ‘functioning of a computer’ (see fact pattern of Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336, 118 USPQ2d 1684, 1689 (Fed. Cir. 2016)) does not constitute operations that a general purpose computer may be programmed/configured to perform, since functioning of a computer instead concerns functions integral to the way computers operate. Regarding the claim(s) ‘as a whole’, the requirement for considering the claim as a whole stems from the fact that the judicial exception alone cannot provide the improvement, and any ‘additional elements’ are not evaluated in a vacuum separate from the weight of those directed to the exception. Consideration must be given to the degree/extent to which the apparent/disclosed improvement, as it is realized in recited claim language, is to the exception itself or otherwise distinct from it and captured by those limitations clearly serving as ‘additional elements’ after analysis at Prong One, in addition to how the ‘additional elements’ weigh in comparison to those limitations directed to the exception. Reference may be made to the recent (08/04/2025) memo affirming analysis set forth in the 2024 PEG (https://www.uspto.gov/sites/default/files/documents/memo-101-20250804.pdf) and consistent with guidance to date. While e.g. identifying a video segment activity label (based on a mentally/visually detected object or otherwise), may have a multitude of uses (furthering an assertion that the identified exception is a “basic tool of scientific and technological work” Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980 (2014); Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012)), it is not in itself a ‘practical application’ distinct from the exception. Additional elements comprising e.g. generic computer hardware, routinely used image/ information acquisition hardware, etc., are usually insufficient for integration in view of MPEP 2106.05(f) and/or (h), since computer implemented process claims generally do not concern any ‘particular machine’ as defined in MPEP 2106.05(b). No additional elements outside of those directed to the exception itself, appear to explicitly/specifically capture/recite any disclosed improvement in technology (MPEP 2106.05(a)). With reference to MPEP 2106.05(a):
It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981))
Even when viewed in combination, the ‘additional elements’ present do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: No), and the claims are directed to the judicial exception. (Revised Step 2A: Yes [Wingdings font/0xE0] Step 2B).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to ‘significantly more’ than the recited exception, i.e., whether any ‘additional element’, or combination of additional elements, adds an inventive concept to the claim. The considerations of Step 2A Prong 2 and Step 2B overlap, but differ in that 2B also requires considering whether the claims feature any “specific limitation(s) other than what is well-understood, routine, conventional activity in the field” (WURC) (MPEP 2106.05(d)). Such a limitation if specifically recited however, must still be excluded from interpretation under any of the Abstract Idea groupings. Step 2B further requires a re-evaluation of any additional elements drawn to extra-solution activity in Step 2A (e.g. gathering video/image(s)) – however no limitations appear directed to any novel collection per se. Limitations not indicative of an inventive concept/ ‘significantly more’ include those that are not specifically recited (instead recited at a high level of generality – e.g. functional claiming of a result/outcome without explicitly reciting how), those that are established as WURC (e.g. generating a video summarization broadly), and/or those that are not ‘additional elements’ by nature of their analysis at Prong One (i.e. reciting the exception) (even limitations that would involve calculating one or more scores (not presently claimed), while individually falling under the math concepts grouping, would not be considered additional elements for integration at Prong Two of 2A or ‘significantly more’ determinations at 2B, since the 2024 PEG makes clear that the exception may involve limitations individually drawn to the mental processes grouping in conjunction with others individually drawn to the mathematical concepts grouping – see linked document/PEG at page 8 in the analysis of Example 47 claim 2). Concerning limitations excluded from serving in ‘significantly more’ determinations on the basis of their being broadly recited and outcome/result oriented absent recited limitations describing how such a result is achieved, Applicant may consider Longitude Licensing Ltd. v. Google LLC, No. 24-1202, (Fed. Cir. April 30, 2025) (available at https://www.cafc.uscourts.gov/opinions-orders/24-1202.OPINION.4-30-2025_2506816.pdf) (see e.g. pages 7-9), and also Rideshare Displays, Inc v. Lyft, Inc., No. 23-2033, (Fed. Cir. September 29, 2025) (https://www.cafc.uscourts.gov/opinions-orders/23-2033.OPINION.9-29-2025_2579953.pdf). Also particularly relevant are the findings of e.g. Recentive Analytics, Inc., v. Fox Corp., Appeal No. 2023-2437, 18 (Fed. Cir. Apr. 18, 2025) available at https://www.cafc.uscourts.gov/opinions-orders/23-2437.OPINION.4-18-2025_2500790.pdf), particularly if it can be asserted (in view of Applicant’s PGPUB [0002]) that the improvement at best involves applying the use of generically recited machine learning techniques/architecture to the field of use that is video summarization. While it is the MPEP that governs Examination and not necessarily case law, these opinions and those referenced therein serve to illustrate the manner in which claims that seek to apply broad classes of machine learning, computer vision, etc., to a ‘new’ field of use (which was the subject matter/emphasis of the 2024 PEG for the case of ML), and/or claim limitations that do not explain/capture how a purported inventive concept/ improvement is actually achieved by limitations excluded from a reading under the exception itself, are not likely to be determined eligible/enforceable. Reference may also be made to the 2024 PEG describing that an improvement/ inventive concept (for ‘significantly more’ determination(s)) cannot be to the judicial exception itself. (Step 2B: No).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21-38 are rejected on the grounds of nonstatutory double patenting as being unpatentable and/or obvious (as may be modified by references of record relied upon below, and similar to the grounds presented in the prior-art based rejections that follow) over one or more claims of:
1) U.S. Patent No. 11,861,495 to parent Application No. 17/201,969 - CON of
2) U.S. Patent No. 10,949,674 to parent Application No. 16/298,549 - CON of
3) U.S. Patent No. 10,229,324 to parent Application No. 14/998,322.
Although the claims at issue are not identical, they are not patentably distinct from each other because claims of reference anticipate and/or render obvious independent claim(s) of the instant application. Reference may be made to Double Patenting rejections as found in the corresponding Non-Final Office Actions for each of the parent applications listed above, all commonly assigned and limited by means of Terminal Disclaimer(s) in view of corresponding predecessor(s). In the interest of compact prosecution, Examiner requests the same for the instant application. The conflicting claims are not patentably distinct from each other for the following reasons:
• Instant claims and claims of reference recite common subject matter, and recite the open ended transitional phrase “comprising” which does not preclude any additional elements recited by claims of reference;
• Language/terminology of instant claim(s) constituting minor/slight variations from the claims of reference, if/where present, require interpretations under Broadest Reasonable Interpretation and/or plain meaning definitions (MPEP 2173 and 2111) equivalent to/met by language of the reference claims in view of that corresponding/shared Specification. While the disclosure of reference may not be used as prior art (Double Patenting concerns the claims of reference), portions of the specification which provide support for reference claims may also be examined and considered when addressing the scope of claim(s) of reference and the issue of whether an instant claim defines an obvious variation or falls within the scope of an invention claimed in the claim(s) of reference. See MPEP 804 with reference to In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970).
• Language/terminology of instant claim(s) otherwise not explicitly recited in claim(s) of reference, constitute limitations met in view of obvious modification to claims of reference for reasons same/similar to those presented in the prior art based rejections below. It would have been obvious to a person of ordinary skill in the art, before the effective filing date, to modify the claims of reference accordingly.
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 of this title, 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.
1. Claims 21-38 are rejected under 35 U.S.C. 103 as being unpatentable over Ji et al. (US 2011/0182469 A1) in view of Chang et al. (US 2017/0238055 A1) (both cited by Applicant).
As to claim 21, Ji discloses at least one memory comprising machine readable instructions to cause one or more processors ([0023-0025]) to at least:
perform shot detection on a video to detect shot boundaries based on content changes in the video and to extract a video segment from the video based on the shot boundaries (generation of multi-frame cubes 22 pertinent to one or more associated human tracks, as determined at hypothesis generation 10, wherein ‘content changes’ correspond to the presence/absence of a human and/or stop/start of an associated track, [0007] “A human detector can process the video frames. A human tracker can also process the video frames. The system can generate multi-frame cubes from tracked humans. The multiple frames cubes are obtained by extracting bounding boxes at a predetermined position from consecutive frames before and after a current frame, leading to a cube containing an action”, [0016] “The temporal dimension of the cube is set to 7 in one implementation as it has been shown that 5-7 frames are enough to achieve a performance similar to the one obtainable with the entire video sequence”, etc., see also those remarks provided above);
input the video segment into a deep learning architecture (Fig. 2, [0007-0008], [0017], [0021] “The developed deep architecture”) the deep learning architecture trained to identify an activity associated with the video segment ([0007], [0008] “Advantages of the preferred embodiments may include one or more of the following. The system applies deep learning of CNNs to 3D video for human action recognition in a real-world environment. The system accurately recognizes human actions involving articulated body motion such as pointing, putting objects, placing telephones to the ear from surveillance videos”, etc.,); and
output data to a compute device, the data including a label corresponding to the activity identified by the deep learning architecture ([0008] “The system accurately recognizes human actions involving articulated body motion such as pointing, putting objects, placing telephones to the ear from surveillance videos”, [0020] “The design essentially applies a linear classifier on the 128D feature vector for action classification”, etc.,), a value representative of a confidence that the label correctly classifies the video segment ([0020] “The design essentially applies a linear classifier on the 128D feature vector for action classification”; While not explicitly disclosed as such, Examiner understands that linear classifier of Ji to compute a numerical score for each class/action – wherein the predicted action/class is that characterized by the highest score/probability/confidence), and a bounding box associated with the activity ([0016] “As each frame contains multiple humans, the human detector 12 and the detection-driven tracker 14 are used to locate human heads. Based on the detection and tracking results, a bounding box for each human that performs action is computed”).
Ji fails to explicitly disclose displaying (if ‘outputting data to a compute device’ broadly interpreted requires as much) the calculated score(s) associated with each action/class (even if it may be argued that the score is representative of a confidence that the associated action/class is a correct one)).
Chang evidences the obvious nature of outputting a confidence associated with one or more generated event/activity labels ([0326] “event-labeling component 1722. Machine learning algorithms are designed to output a measure of confidence. For the most part, this corresponds to the distance from a separating hyperplane in the feature space. In embodiments, one may define a threshold for confidence. If an example is labeled by the machine and has confidence above the threshold, the event goes into the canonical event datastore 210 and nothing further is done. If an example has a confidence score below the threshold, then the system may retrieve the video corresponding to this candidate event, and ask a human operator to provide a judgment. The system asks two separate human operators for labels. If the given labels agree, the event goes into the canonical event datastore 210. If they do not, a third person, known as the supervisor, is contacted for final opinion. The supervisor's decision may be final. The canonical event datastore 210 may contain both human marked and completely automated markings. The system may use both types of marking to further train the pattern recognition algorithms. Event labeling is similar to the canonical event datastore 210, except that sometimes one may either 1) develop the initial gold standard set entirely by hand, potentially with outside experts, or 2) limit the gold standard to events in the canonical event datastore 210 that were labeled by hand, since biases may exist in the machine labeled data”).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date, to modify the system and method of Ji so as to output as data to a compute device broadly, a value representative of a confidence that the label correctly classifies the video segments as taught/suggested in Chang, the motivation as similarly taught/suggested therein that such a confidence may serve as a basis for initiating human/manual validation/ review/correction improving overall system accuracy. It would have further been obvious to a person of ordinary skill in the art, before the effective filing date, to modify the system and method of Ji as proposed to further display those various outputs as taught/suggested by Chang readily extended to others (e.g. bounding box, and activity label), the motivation as similarly suggested therein and readily understood by POSITA that such a display would serve as a means for improving model/system explainability.
As to claim 22, Ji in view of Chang teaches/suggests the CRM of claim 21.
Ji in view of Chang further teaches/suggests the CRM wherein the deep learning architecture includes a convolutional neural network (Ji 3D-CNN 24).
As to claim 23, Ji in view of Chang teaches/suggests the CRM of claim 21.
Ji in view of Chang further teaches/suggests the CRM wherein the label is one of a
plurality of specified labels (Ji [0008] “The system accurately recognizes human actions involving articulated body motion such as pointing, putting objects, placing telephones to the ear from surveillance videos”).
As to claim 24, Ji in view of Chang teaches/suggests the CRM of claim 21.
Ji in view of Chang further teaches/suggests the CRM wherein the instructions are to cause the one or more processors to identify an object associated with the video segment (Ji [0007] “A human tracker can also process the video frames”, [0016] “As each frame contains multiple humans, the human detector 12 and the detection-driven tracker 14 are used to locate human heads. Based on the detection and tracking results, a bounding box for each human that performs action is computed”).
As to claim 25, Ji in view of Chang teaches/suggests the CRM of claim 24.
Ji in view of Chang further teaches/suggests the CRM wherein the bounding box is associated with the object (Ji [0016] – see also Fig. 5 of the related NPL, illustrating different colored bounding boxes and track IDs for each different person/head).
As to claim 26, Ji in view of Chang teaches/suggests the CRM of claim 24.
Ji in view of Chang further teaches/suggests the CRM wherein the object corresponds to a person (see Ji above).
As to claim 27, Ji in view of Chang teaches/suggests the CRM of claim 21.
Ji in view of Chang further teaches/suggests the CRM wherein the value representative of the confidence is a probability value (Chang [0329] “Probabilistic outputs (which measure degree of confidence) assist in this error detection/correction” (see also [00128], [00195], etc., of Specification as filed for 14/634,070 affirming support prior to Applicant’s EFD)).
As to claim 28, this claim is the apparatus claim corresponding to the method of claim 21 and is rejected accordingly. For corresponding structure see Ji Fig. 3, and [0024-0025].
As to claims 29-34, these claims are the apparatus claims corresponding to method claims 22-27 respectively, and are rejected accordingly.
As to claim 35, this claim is an apparatus claim similarly rejected in view of that disclosure as applied in the rejection of claim 21. Claim 35 differs in that the deep learning architecture (wherein Ji’s hypothesis generation sub-architecture 10 and classification sub-architecture 20 in the aggregate are equivalent) is required to detect an object in the video (see Ji human detection 12 and tracking 14, [0016], also e.g. Fig. 5 of the associated NPL (NPL citation No. X in the 10/16/2025 PTO-892, “3D Convolutional Neural Networks for Human Action Recognition”); with note that this detecting is not mutually exclusive with providing a label in association with such a detection, and also claim language frequently encountered in USPC 382 often affords ‘object’ a scope comprising ‘human’, and Applicant’s claim 37 affirms such a reading) associated with that activity/action label/class and confidence score (see claim 21). While Examiner would assert that he ‘output[ing]’ of such a bounding box is met even if done as an intermediate step, similar modification as that presented above for the case of claim 21, may be readily extended to the associated bounding boxes for each frame of those linked so as to form the ‘event segments’ in Ji’s post-processing 30. Modification in this respect would serve to provide model explainability, as the final event segments, for each frame, would illustrate the bounding box that contributed to the activity/class label. See also e.g. Fig. 2 at page 1475 of Turaga et al. (NPL citation No. W in the accompanying PTO-892).
As to claims 36-38, these claims are the apparatus claims comprising limitations corresponding to those of method claims 22, 26 and 27 respectively, and are rejected accordingly.
Additional References
Prior art made of record and not relied upon that is considered pertinent to applicant's disclosure:
Additionally cited references (see attached PTO-892) otherwise not relied upon above have been made of record in view of the manner in which they evidence the general state of the art proximate or prior to Applicant’s Effective Filing Date.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IAN L LEMIEUX whose telephone number is (571)270-5796. The examiner can normally be reached Mon - Fri 9:00 - 6:00 EST.
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/IAN L LEMIEUX/Primary Examiner, Art Unit 2669
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