Markerless tracking of human pose is a hard yet relevant problem. In this paper, we derive an efficient filtering algorithm for tracking human pose at 4-10 frames per second using...
Varun Ganapathi, Christian Plagemann, Sebastian Th...
In this paper we develop a computer vision-based system to transfer human motion from one subject to another. Our system uses a network of eight calibrated and synchronized camera...
German K. M. Cheung, Simon Baker, Jessica K. Hodgi...
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 kinemat...
Edilson de Aguiar, Christian Theobalt, Carsten Sto...
This work presents a marker-less motion capture system that incorporates an approach to smoothly adapt a generic model mesh to the individual shape of a tracked person. This is don...