Evaluation device for re-identification and corresponding method, system and computer program

    公开(公告)号:US12061674B2

    公开(公告)日:2024-08-13

    申请号:US17446173

    申请日:2021-08-27

    CPC分类号: G06F18/22 G06V20/40 G06V20/48

    摘要: Examples relate to an evaluation device for re-identification and to a corresponding method, system and computer program. The evaluation device comprises processing circuitry being configured to obtain a plurality of transformed re-identification codes, each transformed re-identification code being associated with a timestamp and location information. Each transformed re-identification code is based on a similarity-preserving transformation of a re-identification code that represents at least a portion of a sample of media data, the media data originating from two or more different sources located in two or more different locations. The processing circuitry is configured to match transformed re-identification codes among the plurality of transformed re-identification codes using a similarity metric to generate one or more tuples of transformed re-identification codes that are similar according to the similarity metric. The processing circuitry is configured to determine one or more sequences of locations associated with the transformed re-identification codes of the one or more tuples of transformed re-identification codes based on the timestamps and location information associated with the transformed re-identification codes of the respective tuple. The processing circuitry is configured to provide information on the one or more sequences of locations.

    Computer-implemented method, data processing apparatus, and computer program for generating three-dimensional pose-estimation data

    公开(公告)号:US12056895B2

    公开(公告)日:2024-08-06

    申请号:US17643849

    申请日:2021-12-13

    摘要: Examples relate to a computer-implemented method, data processing apparatus and computer program for generating three-dimensional pose-estimation data. The method comprises obtaining video data of a plurality of cameras, the video data showing a movement of one or more persons, as perceived from a plurality of angles of observation. The method comprises generating two-dimensional pose-estimation data of the one or more persons using a machine-learning model that is suitable for performing two-dimensional pose-estimation based on the video data. The method comprises generating three-dimensional pose-estimation data of the one or more persons based on the two-dimensional pose-estimation data of the one or more persons. The two-dimensional and three-dimensional pose-estimation data is defined by one or more points on the body of the one or more persons. The method comprises providing an animation of the movement of the one or more persons by illustrating the movement of the one or more points on the body of the one or more persons overlaid over the video data. The method comprises providing a user interface for a user to adjust the position of the one or more points on the body of the one or more persons, the user interface being based on the illustration of the movement of the one or more points that is overlaid over the video data.