期刊
IEEE SENSORS JOURNAL
卷 16, 期 3, 页码 773-781出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2015.2487358
关键词
Human action recognition; real-time human action recognition system; depth camera sensor; wearable inertial sensor; sensor fusion
资金
- National Science Foundation [CNS-1150079]
This paper presents a human action recognition system that runs in real time and simultaneously uses a depth camera and an inertial sensor based on a previously developed sensor fusion method. Computationally efficient depth image features and inertial signals features are fed into two computationally efficient collaborative representative classifiers. A decision-level fusion is then performed. The developed real-time system is evaluated using a publicly available multimodal human action recognition data set by considering a comprehensive set of human actions. The overall classification rate of the developed real-time system is shown to be >97%, which is at least 9% higher than when each sensing modality is used individually. The results from both offline and real-time experimentations demonstrate the effectiveness of the system and its real-time throughputs.
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