Method and system for enhancing use of two-dimensional video analytics by using depth data

    公开(公告)号:US11303877B2

    公开(公告)日:2022-04-12

    申请号:US16539888

    申请日:2019-08-13

    摘要: Methods, systems, and techniques for enhancing use of two-dimensional (2D) video analytics by using depth data. Two-dimensional image data representing an image comprising a first object is obtained, as well as depth data of a portion of the image that includes the first object. The depth data indicates a depth of the first object. An initial 2D classification of the portion of the image is generated using the 2D image data without using the depth data. The initial 2D classification is stored as an approved 2D classification when the initial 2D classification is determined consistent with the depth data. Additionally or alternatively, a confidence level of the initial 2D classification may be adjusted depending on whether the initial 2D classification is determined to be consistent with the depth data, or the depth data may be used with the 2D image data for classification.

    Anomaly detection method, system and computer readable medium

    公开(公告)号:US11302117B2

    公开(公告)日:2022-04-12

    申请号:US16844712

    申请日:2020-04-09

    IPC分类号: G06V40/20 G06V20/40 G06V20/52

    摘要: A method of detecting an anomaly is provided, including dividing each frame of a video stream into a plurality of cells; in each cell formulate statistics based on metadata generated for the frame, the metadata related to presence of an object in the cell, velocity of objects in the cell, direction of motion of objects in the cell, and classification of objects in the cell; and using the formulated statistics to determine when the anomalous activity has occurred in one of the cells of the plurality of cells.

    ANOMALY DETECTION METHOD, SYSTEM AND COMPUTER READABLE MEDIUM

    公开(公告)号:US20200327313A1

    公开(公告)日:2020-10-15

    申请号:US16844712

    申请日:2020-04-09

    IPC分类号: G06K9/00

    摘要: A method of detecting an anomaly is provided, including dividing each frame of a video stream into a plurality of cells; in each cell formulate statistics based on metadata generated for the frame, the metadata related to presence of an object in the cell, velocity of objects in the cell, direction of motion of objects in the cell, and classification of objects in the cell; and using the formulated statistics to determine when the anomalous activity has occurred in one of the cells of the plurality of cells.