A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
Local and Global Skeleton Fitting Techniques for Optical Motion Capture
CAPTECH '98 Proceedings of the International Workshop on Modelling and Motion Capture Techniques for Virtual Environments
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Skeletal Parameter Estimation from Optical Motion Capture Data
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A real-time sequential algorithm for human joint localization
SIGGRAPH '05 ACM SIGGRAPH 2005 Posters
SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Towards a low cost multi-camera marker based human motion capture system
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
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We present a novel fully-automatic approach for estimating an articulated skeleton of a moving subject and its motion from body marker trajectories that have been measured with an optical motion capture system. Our method does not require a priori information about the shape and proportions of the tracked subject, can be applied to arbitrary motion sequences, and renders dedicated initialization poses unnecessary. To serve this purpose, our algorithm first identifies individual rigid bodies by means of a variant of spectral clustering. Thereafter, it determines joint positions at each time step of motion through numerical optimization, reconstructs the skeleton topology, and finally enforces fixed bone length constraints. Through experiments, we demonstrate the robustness and efficiency of our algorithm and show that it outperforms related methods from the literature in terms of accuracy and speed.