Scaled Motion Dynamics for Markerless Motion Capture

Bodo Rosenhahn, Thomas Brox, Hans-Peter Seidel
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
This work proposes a way to use a-priori knowledge on motion dynamics for markerless human motion capture (MoCap). Specifically, we match tracked motion patterns to training patterns in order to predict states in successive frames. Thereby, modeling the motion by means of twists allows for a proper scaling of the prior. Consequently, there is no need for training data of different frame rates or velocities. Moreover, the method allows to combine very different motion patterns. Experiments in
more » ... . Experiments in indoor and outdoor scenarios demonstrate the continuous tracking of familiar motion patterns in case of artificial frame drops or in situations insufficiently constrained by the image data.
doi:10.1109/cvpr.2007.383128 dblp:conf/cvpr/RosenhahnBS07 fatcat:zbrcvgngrnb7jeglzgzodkvgpy