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학술대회 Kick Recognition System Using Dual RGB-D Cameras
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홍성진, 김명규, 김예진
International Conference on Video and Image Processing (ICVIP) 2018, pp.12-16
18KS1200, 청소년용 실감 체험형 스포츠 통합플랫폼 기술 개발, 김명규
This paper introduces a kick recognition system based on human body detection using dual RGB-D cameras. Recently, the availability of RGB-D cameras makes it possible to get the human body joints that are informative for activity analysis. However, single camera-based approaches enforce frontal-oriented action due to the occlusion problem. Using dual RGB-D cameras and a smart sandbag, the proposed system detects major joints and recognizes various kick actions from a general user in real time. For each camera, our system detects salient body parts in a kick action such as a head and feet. A local detector trained with a supervised model is used for the head detection. The detected body parts are converted into a quadtree-structured graph model to detect feet using accumulative geodesic distance (AGD). To deal with the occlusion by the sandbag, our system compares the result of each camera and selects the most reliable one based on AGD. For the kick recognition, a finite-state machine is adopted to track and to segment continuous kick movements into different states. Considering a viewpoint change and a variable kick speed, fixed size descriptors are constructed from the interpolated action to recognize user kicks. We evaluated our system using various kick actions in taekwondo and achieved a high recognition rate of 92%.
KSP 제안 키워드
Body joints, Body parts, Geodesic distance, Graph model, Human body detection, RGB-D camera, Real-Time, Recognition System, Recognition rate, Supervised model, activity analysis