Patent ID: 11948400
Assignee: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. An action detection method based on a human skeleton feature, comprising:
(S1) extracting a series of keypoints that represent the human skeleton feature of each target person from every frame image in the provided video stream;
(S2) for each target person in each frame image, calculating, by using the human skeleton feature, the center point of the human structure and an approximate area of rigid motion, which serves as a calculated value from the skeleton feature state;
estimating the center point of the human structure and an approximate area of rigid motion in the next adjacent frame according to the calculated value, which serves as an estimated value from the skeleton feature state; the center point of the human structure and the approximate area of rigid motion respectively are an average coordinate point and a minimum bounding rectangle of the keypoints whose motion amplitude between frames is less than a predetermined threshold in the human skeleton feature;
(S3) performing target matching according to the estimated value and calculated value from the skeleton feature state of each frame image; correlating the human skeleton features belonging to the same target person in each frame image based on a matching result, which is used to generate a sequence of skeleton feature for each target person; correlating the features of each keypoint in the sequence of skeleton feature in the temporal domain, which is used to obtain a spatial-temporal domain skeleton feature;
(S4) inputting the spatial-temporal domain skeleton feature of the target person into a trained action detection model to obtain a corresponding action category, the action detection model is a deep learning model, which takes the spatial-temporal domain skeleton feature of the target person as input and is used to predict the corresponding action category.