Chen Chen — Publications

C. Chen, R. Jafari, and N. Kehtarnavaz, “A Real-Time Human Action Recognition System Using Depth and Inertial Sensor Fusion,” IEEE Sensors Journal, vol. 16, no. 3, pp. 773-781, February 2016. (doi: 10.1109/JSEN.2015.2487358)
  • Abstract:
    This paper presents a human action recognition system that runs in real-time and uses a depth camera and an inertial sensor simultaneously 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 dataset by considering a comprehensive set of human actions. The overall classification rate of the developed real-time system is shown to be more than 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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