High-precision and high-speed motion capture combining heterogeneous cameras

Today optical motion capture system is becoming an essential tool for motion analysis, synthesis, and character animation. This paper focuses on improving the ability of current passive optical motion capture systems, which provides the highest precision and flexibility with the lowest interference among current motion capture technologies but has two major drawbacks. Firstly, it usually requires expensive post-processing computation including reconstruction and labeling. The second problem is that it is difficult to achieve both high precision and high frame rate at the same time due to the limitation of data transmission rate, that is, high-resolution cameras have low frame rate and vice versa. In this paper, we try to solve these problems by combining cameras of different types that complement the limitations of each others. The marker positions measured by the high-resolution cameras correct the low-precision data from high-speed cameras, which in turn helps real-time tracking of markers by inserting new data at higher frame rate. The proposed method is implemented on a PC cluster and experimental results show that we can obtain high-precision data even for high-speed motions. We also demonstrate the real-time joint angle computation using the real-time tracking capability.

[1]  Christopher G. Atkeson,et al.  Adapting human motion for the control of a humanoid robot , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[2]  Katsu Yamane,et al.  Natural Motion Animation through Constraining and Deconstraining at Will , 2003, IEEE Trans. Vis. Comput. Graph..

[3]  Jessica K. Hodgins,et al.  Interactive control of avatars animated with human motion data , 2002, SIGGRAPH.

[4]  Jessica K. Hodgins,et al.  Motion capture-driven simulations that hit and react , 2002, SCA '02.

[5]  Katsu Yamane,et al.  Optical motion capture system with pan-tilt camera tracking and real time data processing , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[6]  Stephen J. Dorgan,et al.  Tracking, modelling and animation in human motion analysis, diagnosis and synthesis , 1998, MULTIMEDIA '98.

[7]  Kazuhito Yokoi,et al.  Generating whole body motions for a biped humanoid robot from captured human dances , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[8]  Xing Chen,et al.  Design of many-camera tracking systems for scalability and efficient resource allocation , 2002 .