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학술지 Implementation of a Virtual Training Simulator Based on 360° Multi-View Human Action Recognition
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저자
권범, 김정환, 이경오, 이양구, 박상준, 이상훈
발행일
201707
출처
IEEE Access, v.5, pp.12496-12511
ISSN
2169-3536
출판사
IEEE
DOI
https://dx.doi.org/10.1109/ACCESS.2017.2723039
협약과제
16MS4700, 병사들에게 실전과 같은 가상훈련 환경을 제공하기 위한 전 방향 이동 지원 상호작용 소프트웨어 기술 개발, 박상준
초록
Virtual training has received a considerable amount of research attention in recent years due to its potential for use in a variety of applications, such as virtual military training, virtual emergency evacuation, and virtual firefighting. To provide a trainee with an interactive training environment, human action recognition methods have been introduced as a major component of virtual training simulators. Wearable motion capture suit-based human action recognition has been widely used for virtual training, although it may distract the trainee. In this paper, we present a virtual training simulator based on 360째 multi-view human action recognition using multiple Kinect sensors that provides an immersive environment for the trainee without the need to wear devices. To this end, the proposed simulator contains coordinate system transformation, front-view Kinect sensor tracking, multi-skeleton fusion, skeleton normalization, orientation compensation, feature extraction, and classifier modules. Virtual military training is presented as a potential application of the proposed simulator. To train and test it, a database consisting of 25 military training actions was constructed. In the test, the proposed simulator provided an excellent, natural training environment in terms of frame-by-frame classification accuracy, action-by-action classification accuracy, and observational latency.
키워드
Human action recognition, Kinect sensor, virtual training simulator
KSP 제안 키워드
Action Classification, Coordinate system transformation, Feature extractioN, Immersive Environment, Kinect Sensor, Military training, Motion capture, Multi-view, Potential applications, Recognition method, Training environment