Tracking people with twists and exponential maps

This paper demonstrates a new visual motion estimation technique that is able to recover high degree-of-freedom articulated human body configurations in complex video sequences. We introduce the use of a novel mathematical technique, the product of exponential maps and twist motions, and its integration into a differential motion estimation. This results in solving simple linear systems, and enables us to recover robustly the kinematic degrees-of-freedom in noise and complex self occluded configurations. We demonstrate this on several image sequences of people doing articulated full body movements, and visualize the results in re-animating an artificial 3D human model. We are also able to recover and re-animate the famous movements of Eadweard Muybridge's motion studies from the last century. To the best of our knowledge, this is the first computer vision based system that is able to process such challenging footage and recover complex motions with such high accuracy.