Using skeleton-based tracking to increase the reliability of optical motion capture

Optical motion capture provides an impressive ability to replicate gestures. However, even with a highly professional system there are many instances where crucial markers are occluded or when the algorithm confuses the trajectory of one marker with that of another. This requires much editing work on the user's part before the complete animation is ready for use. In this paper, we present an approach to increasing the robustness of a motion capture system by using an anatomical human model. It includes a reasonably precise description of the skeleton's mobility and an approximated envelope. It allows us to accurately predict the 3-D location and visibility of markers, thus significantly increasing the robustness of the marker tracking and assignment, and drastically reducing--or even eliminating--the need for human intervention during the 3-D reconstruction process.