Marker-less Deformable Mesh Tracking for Human Shape and Motion Capture

We present a novel algorithm to jointly capture the motion and the dynamic shape of humans from multiple video streams without using optical markers. Instead of relying on kinematic skeletons, as traditional motion capture methods, our approach uses a deformable high-quality mesh of a human as scene representation. It jointly uses an imagebased 3D correspondence estimation algorithm and a fast Laplacian mesh deformation scheme to capture both motion and surface deformation of the actor from the input video footage. As opposed to many related methods, our algorithm can track people wearing wide apparel, it can straightforwardly be applied to any type of subject, e.g. animals, and it preserves the connectivity of the mesh over time. We demonstrate the performance of our approach using synthetic and captured real-world video sequences and validate its accuracy by comparison to the ground truth.

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Edilson de Aguiar, Christian Theobalt, Carsten Stoll, Hans-Peter Seidel
• Keywords: Captured Real-world Video, Computer Vision, Correspondence Estimation Algorithm, CVPR 2007, Input Video Footage, Laplacian Mesh Deformation, Traditional Motion Capture