Marker-less Motion Capture
Personal Homepage: http://www.tnt.uni-hannover.de/staff/rosenhahn/
Motion capturing (MoCap) comprises techniques for recording and analyzing human movements in image sequences. In biomechanical settings, it is aimed at analyzing captured data to quantify the movement of body segments, e.g. for clinical studies, or to help athletes to understand and improve their performance. It has also grown increasingly important as source of motion data for computer animation. Well known and commercially available marker-based tracking systems exist, e.g. those provided by Motion Analysis, Vicon or Simi. The use of markers comes along with intrinsic problems, e.g. incorrect tracking of markers, tracking failures, the need for special laboratory environments and lighting conditions and the fact that people do not feel comfortable with markers attached to the body. This often leads to unnatural motion patterns. As well, marker-based systems are designed to track the motion of the markers themselves, and thus it must be assumed that the recorded motion of the markers is identical to the motion of the underlying human segments. Since human segments are not truly rigid this assumption may cause problems, especially in highly dynamic movements typically seen in sporting activities. For these reasons, marker-less tracking is an important field of research that requires knowledge in biomechanics, computer vision and computer graphics.
The research group deals with different aspects regarding marker-less motion capture, e.g. pose estimation, image segmentation, surface modeling, surface morphing and texture driven tracking. Foundations and experiences of my PhD-Thesis and PostDoc in New Zealand are crucial for our ongoing research.
Mentor in Saarbrücken: Professor Hans-Peter Seidel