LEARNING APPARATUS, ESTIMATION APPARATUS, LEARNING METHOD, AND NON-TRANSITORY STORAGE MEDIUM

    公开(公告)号:US20230298445A1

    公开(公告)日:2023-09-21

    申请号:US18010158

    申请日:2020-06-24

    CPC classification number: G08B13/19613 G08B13/19604

    Abstract: The present invention provides a learning apparatus (10) including: an acquisition unit (11) that acquires an image; a similarity computation unit (12) that computes a similarity between the acquired image, and a first image being accumulated in advance and indicating an abnormal state; a registration unit (13) that registers, as a second image indicating a normal state, the acquired image whose similarity is equal to or less than a first reference value; and a learning unit (14) that generates an estimation model for discriminating between normal and abnormal by machine learning using the first image and the second image.

    RETRIEVAL DEVICE, CONTROL METHOD, AND NON-TRANSITORY STORAGE MEDIUM

    公开(公告)号:US20220222967A1

    公开(公告)日:2022-07-14

    申请号:US17610200

    申请日:2020-05-08

    Abstract: A retrieval apparatus (2000) is accessible to a storage region (50) in which a plurality of pieces of object information (100) are stored. The object information (100) includes a feature value set (104) being a set of a plurality of feature values acquired regarding an object. The retrieval apparatus (2000) acquires a feature value set (retrieval target set (60)) being a retrieval target, and determines the object information (100) having the feature value set (104) similar to the retrieval target set (60) by comparing the retrieval target set (60) with the feature value set (104). Herein, in a case where a feature value set satisfies a predetermined condition, the retrieval apparatus (2000) performs comparison between the feature value set and another feature value set by using a part of feature values within the feature value set. Further, the retrieval apparatus (2000) outputs output information relating to the determined object information (100).

    SEARCH APPARATUS, SEARCH METHOD, AND NON-TRANSITORY STORAGE MEDIUM

    公开(公告)号:US20200242155A1

    公开(公告)日:2020-07-30

    申请号:US16755930

    申请日:2018-10-15

    Abstract: A search apparatus (10) including a storage unit (11) that stores video index information including correspondence information which associates a type of one or a plurality of objects extracted from a video with a motion of the object, an acquisition unit (12) that acquires a search key associating the type of one or the plurality of objects as a search target with the motion of the object, and a search unit (13) that searches the video index information on the basis of the search key is provided.

    ANALYSIS APPARATUS, ANALYSIS METHOD, AND STORAGE MEDIUM

    公开(公告)号:US20190244342A1

    公开(公告)日:2019-08-08

    申请号:US16382282

    申请日:2019-04-12

    Abstract: The analysis apparatus (2000) includes a co-appearance event extraction unit (2020) and a frequent event detection unit (2040). The co-appearance event extraction unit (2020) extracts co-appearance events of two or more persons from each of a plurality of sub video frame sequences. The sub video frame sequence is included in a video frame sequence. The analysis apparatus (2000) may obtain the plurality of sub video frame sequences from one or more of the video frame sequences. The one or more of the video frame sequences may be generated by one or more of surveillance cameras. Each of the sub video frame sequences has a predetermined time length. The frequent event detection unit (2040) detects co-appearance events of the same persons occurring at a frequency higher than or equal to a pre-determined frequency threshold.

    ANALYSIS APPARATUS, ANALYSIS METHOD, AND STORAGE MEDIUM

    公开(公告)号:US20190035106A1

    公开(公告)日:2019-01-31

    申请号:US16080745

    申请日:2017-02-13

    Abstract: Provided is an analysis apparatus (10) including a person extraction unit (11) that analyzes video data to extract a person, a time calculation unit (12) that calculates a continuous appearance time period for which the extracted person has been continuously present in a predetermined area and a reappearance time interval until the extracted person reappears in the predetermined area for each extracted person, and an inference unit (13) that infers a characteristic of the extracted person on the basis of the continuous appearance time period and the reappearance time interval.

    ANALYSIS APPARATUS, ANALYSIS METHOD, AND STORAGE MEDIUM

    公开(公告)号:US20190026882A1

    公开(公告)日:2019-01-24

    申请号:US15755607

    申请日:2015-08-28

    Abstract: The analysis apparatus (2000) includes a co-appearance event extraction unit (2020) and a frequent event detection unit (2040). The co-appearance event extraction unit (2020) extracts co-appearance events of two or more persons from each of a plurality of sub video frame sequences. The sub video frame sequence is included in a video frame sequence. The analysis apparatus (2000) may obtain the plurality of sub video frame sequences from one or more of the video frame sequences. The one or more of the video frame sequences may be generated by one or more of surveillance cameras. Each of the sub video frame sequences has a predetermined time length. The frequent event detection unit (2040) detects co-appearance events of the same persons occurring at a frequency higher than or equal to a pre-determined frequency threshold.

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