Remote physiotherapy treatments using wireless body sensor networks
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Markerless human motion tracking with a flexible model and appearance learning
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Human motion modeling using multivision
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Semi-automated human body 3D animator
International Journal of Computer Applications in Technology
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Motion capture has important applications in different areas such as biomechanics, computer animation, and human-computer interaction. Current motion capture methods use passive markers that are attached to different body parts of the subject and are therefore intrusive in nature. In applications such as pathological human movement analysis, these markers may introduce an unknown artifact in the motion, and are, in general, cumbersome. We present computer vision based methods for performing markerless human motion capture. We model the human body as a set of super-quadrics connected in an articulated structure and propose algorithms to estimate the parameters of the model from video sequences. We compute a volume data (voxel) representation from the images and combine bottom-up approach with top down approach guided by our knowledge of the model. We propose a tracking algorithm that uses this model to track human pose. The tracker uses an iterative framework akin to an Iterated Extended Kalman Filter to estimate articulated human motion using multiple cues that combine both spatial and temporal information in a novel manner. We provide preliminary results using data collected from 8-16 cameras. The emphasis of our work is on models and algorithms that are able to scale with respect to the requirement for accuracy. Our ultimate objective is to build an end-to-end system that can integrate the above mentioned components into a completely automated markerless motion capture system.