DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) were submitted on 12/23/2024, 07/31/2025, and 01/21/2025. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Status
Claim(s) 1, 5, and 6 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kim (US 20180121732 A1)
Claims 2-4 are objected to as being dependent upon a rejected base claim but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim Rejections - 35 USC § 102
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 5, and 6 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kim (US 20180121732 A1)
Regarding claims 1, 5, and 6 Kim discloses [Claim 1: A generation program (¶16 “generate a composition image”) for causing a computer to execute processing comprising: (¶49 “a conventional general purpose processor (e.g., a CPU or an application processor)”)]
[Claim 5: A generation method (¶16 “generate a composition image”) implemented by a computer, the generation method comprising: (¶49 “a conventional general purpose processor (e.g., a CPU or an application processor)”)]
[Claim 6: An information processing apparatus comprising: a control unit configured to perform processing including: (¶49 “a conventional general purpose processor (e.g., a CPU or an application processor)”)]
acquiring video data; (¶55 “The video inputter 110 may receive a video. The video may include a plurality of images (or frames).”)
specifying, by inputting the acquired video data to a machine learning model, a class of an action of a person included in the video data (¶110 “The recognition result provider 240 may provide state information of a person included in the video such as ‘during exercise 241’ ‘emergency 242’, ‘break 243’, ‘eating 244’, ‘sleeping 245’ as state information of an object by text, voice, video,”) and a degree of reliability of the class; and (¶126 “At this time, the model update unit 260 may identify recognition correction level based on a result recognized by using the recognition model”)
generating, based on the specified degree of reliability, question information related to the specified class. (¶127 “when the recognition result provider 240 outputs a recognition result using the data recognition model, the model update unit 260 may present to the user a question inquiring whether the recognition result is correct, and identify whether to update or not based on the user's response regarding the inquiry.”)
Allowable Subject Matter
Claims 2-4 are objected to as being dependent upon a rejected base claim but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Long (US 20200074294 A1) discloses methods, non-transitory computer readable media, and systems that use machine-learning techniques to facilitate the creation, timing of distribution, or follow-up actions for digital surveys. In one such implementation, the disclosed methods, non-transitory computer readable media, and systems use a survey-creation-machine learner to generate suggested survey questions for an administrator designing a digital survey. Additionally, in some implementations, the disclosed methods, non-transitory computer readable media, and systems use specialized machine learners to suggest timeframes in which to send digital surveys or to suggest action items to follow up on responses to the survey questions.
Zheng (US 20200205697 A1) discloses a video-based fall risk assessment system. During operation, this fall risk assessment system can receive a sequence of video frames including a person being monitored for fall risk assessment. The system next generates a sequence of action labels for the sequence of video frames by, for each video frame in the sequence of video frames: estimating a pose of the person within the video frame; and classifying the estimated pose as a given action among a set of predetermined actions. Next, the system identifies a subset of action labels within the sequence of action labels. The system next extracts a set of gait features for the person from a subset of video frames within the sequence of video frames corresponding to the subset of action labels. Subsequently, the system analyzes the set of extracted gait features to generate a fall risk assessment for the person. In some embodiments, the sequence of video frames is captured during a predetermined time period, such as an hour, a day, or a week.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL KIM MAIDEN whose telephone number is (703)756-1264. The examiner can normally be reached Monday - Friday 7:30 am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen Koziol can be reached at 4089187630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL KIM MAIDEN/Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
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