MEASUREMENT APPARATUS AND MEASUREMENT METHOD

    公开(公告)号:US20220366560A1

    公开(公告)日:2022-11-17

    申请号:US17642903

    申请日:2020-08-27

    Abstract: Provided is a measurement apparatus including a processor and a storage unit. The storage unit holds measurement data of each time point which is obtained by a photographing apparatus, and temporal-spatial constraints. The processor extracts a position of an object from the measurement data of each time point, determines whether the object satisfies the temporal-spatial constraints, and determines, based on a result of the determination on whether the object satisfies the temporal-spatial constraints, whether the object is an analysis target.

    INFORMATION PROCESSING APPARATUS AND DETERMINATION RESULT OUTPUT METHOD

    公开(公告)号:US20230005161A1

    公开(公告)日:2023-01-05

    申请号:US17793993

    申请日:2020-09-10

    Abstract: In a motion analysis apparatus 101, a data input unit 205 acquires a first imaging result and a second imaging result. in the motion analysis apparatus 101, a skeleton recognition unit 206 recognizes skeleton positions of a subject using the first imaging. result acquired by the data input unit 205, and recognizes skeleton positions of the subject using the second imaging result acquired by the data input unit 205. A motion period extraction unit 403 extracts a period from a start of a motion to an end of the motion as a range of data for comparing skeleton feature points recognized by the skeleton recognition unit 206. The similarity calculation unit 401 compares skeleton feature points recognized for an input from a depth camera with skeleton feature points recognized for an input from an RGB camera to calculate similarities, and outputs a determination result based on the similarities.

    DATA ANALYSIS APPARATUS, DATA ANALYSIS METHOD, AND DATA ANALYSIS PROGRAM

    公开(公告)号:US20220246302A1

    公开(公告)日:2022-08-04

    申请号:US17621884

    申请日:2020-06-22

    Abstract: An object of the invention is to harmonize prediction accuracy and an analysis time of an ensemble model. Therefore, when performing data analysis using an ensemble model 300 that makes an inference by integrating inferences by first to n-th models, an i-th model (1≤i≤n) constituting the ensemble model 300 is selected from an i-th model group of the model data, at least one model group of the first to n-th model groups includes a plurality of models, and the first to n-th models capable of constituting an ensemble model satisfying a performance requirement for data analysis and a constraint requirement for time required for the data analysis are selected from the first to n-th model groups 301 to 303.

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