Human Motion Tracking based on Complementary Kalman Filter

Zhibo Wang, Lin Yang, Zhipei Huang1, Jiangkang Wu1, Zhiqiang Zhang, Lixin Sun

  • 1University of Chinese Academy of Sciences

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Contributed Papers (Poster)

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Abstract

Miniaturized Inertial and Magnetic Sensor Unit (IMU) has been widely used in many motion capturing applications. In order to overcome stability and noise problems of IMU, a lot of efforts have been made to develop appropriate data fusion method to obtain reliable orientation estimation from IMU data. This article presents a method which models the errors of orientation, gyroscope bias and magnetic disturbance, and compensate the errors of state variables with complementary Kalman filter in a body motion capture system. Experimental results have shown that the proposed method significantly reduces the accumulative orientation estimation errors.

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