Skeleton-based Motion Capture for Robust Reconstruction of Human Motion

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 part of the animator before the virtual characters are ready for their screen debuts. In this paper, we present an approach to increasing the robustness of a motion capture system by using a sophisticated anatomic human model. It includes a 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.