APPARATUS AND METHOD FOR TRACKING MULTIPLE OBJECTS

    公开(公告)号:US20210183074A1

    公开(公告)日:2021-06-17

    申请号:US17037399

    申请日:2020-09-29

    Abstract: Disclosed is a method of tracking multiple objects included in an image using a multi-object tracking apparatus including an integrated similarity neural network, the method including setting a tracking area in an input image, extracting at least one object candidate for a target object from the tracking area; extracting reference features for the target object, the object candidate, and the tracking area, selecting two of the target object, the object candidate, and the tracking area to evaluate similarity based on the reference features; allocating the object candidate to the target object on the basis of the evaluated similarity; and tracking the target object on the basis of a location of the allocated object candidate.

    EARLY EARTHQUAKE DETECTION APPARATUS AND METHOD

    公开(公告)号:US20210247531A1

    公开(公告)日:2021-08-12

    申请号:US17168066

    申请日:2021-02-04

    Abstract: An early earthquake detection method may comprise acquiring a frame image from a camera; acquiring a vibration signal from the frame image; removing a noise signal due to vibration of the camera from the vibration signal; acquiring a motion signal obtained by magnifying subtle motions from the noise signal-removed vibration signal; extracting vibration characteristics from the motion signal; estimating an occurrence of an earthquake by extracting a peak signal from the vibration characteristics; and determining whether an earthquake occurs by receiving earthquake estimation information from at least one other camera located within a certain range.

    ACTION RECOGNITION METHOD AND APPARATUS BASED ON SPATIO-TEMPORAL SELF-ATTENTION

    公开(公告)号:US20220164569A1

    公开(公告)日:2022-05-26

    申请号:US17512544

    申请日:2021-10-27

    Abstract: The present disclosure provides an action recognition method including: acquiring video features for input videos; generating a bounding box surrounding a person who may be a target for an action recognition; pooling the video features based on bounding box information; extracting at least one spatial feature map from pooled video features; extracting at least one temporal feature map from pooled video features; concatenating the at least one spatial feature map and the at least one temporal feature map to generate a concatenated feature map; and performing a human action recognition based on the concatenated feature map.

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