Multimodal Gesture Recognition for Mascot Robot System Based on Choquet Integral Using Camera and 3D Accelerometers Fusion
Yongkang Tang*, Hai An Vu*, Phuc Q. Le*, Daisuke Masano*,
OoHan Thet*, Chastine Fatichah*, Zhentao Liu*,
Masashi Yamaguchi*, Martin Leonard Tangel*,
Fangyan Dong*, Yoichi Yamazaki**, and Kaoru Hirota*
*Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama, Kanagawa 226-8502, Japan
**Department of Electrical, Electronic & Information Engineering, Faculty of Engineering, Kanto Gakuin University, 1-50-1 Mutsuura-higashi, Kanazawa-ku, Yokohama, Kanagawa 236-8501, Japan
A multimodal gesture recognition method for mascot robot system is proposed based on Choquet integral by fusing camera and 3D accelerometer data. The optimization of two fuzzy measures in the training phase for two recognition units, i.e., camera-based and accelerometer-based units, obtains enough recognition rate of 92.7% for 8 types of gestures by improving the recognition rate approximate 20% compared with that of each unit. The proposed method targets casual communication from humans to robots by integrating nonverbal gesture messages and verbal messages.
OoHan Thet, Chastine Fatichah, Zhentao Liu,
Masashi Yamaguchi, Martin Leonard Tangel,
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