Modeling joint constraints for an articulated 3D human body model with artificial correspondences in ICP

This paper describes a new approach for modeling joints in an articulated 3D body model for tracking of the configuration of a human body. The used model consists of a set of rigid generalized cylinders. The joints between the cylinders are modeled as artificial point correspondences within the ICP (iterative closest point) tracking algorithm, which results in a set of forces and torques maintaining the model constraints. It is shown that different joint types with different degrees of freedom can be modeled with this approach. Experiments show the functionality and robustness of the presented model

[1]  Trevor Darrell,et al.  3-D articulated pose tracking for untethered diectic reference , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

[2]  Thomas B. Moeslund,et al.  A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..

[3]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[4]  Sebastian Lang,et al.  Improving adaptive skin color segmentation by incorporating results from face detection , 2002, Proceedings. 11th IEEE International Workshop on Robot and Human Interactive Communication.

[5]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[6]  David A. Forsyth,et al.  Finding and tracking people from the bottom up , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[7]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[8]  Sebastian Lang,et al.  Multi-modal anchoring for human-robot interaction , 2003, Robotics Auton. Syst..

[9]  Aude Billard,et al.  Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM , 2005, ICML.

[10]  James W. Davis,et al.  The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  David Demirdjian Enforcing Constraints for Human Body Tracking , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.

[12]  Tieniu Tan,et al.  Recent developments in human motion analysis , 2003, Pattern Recognit..

[13]  Hedvig Sidenbladh Probabilistic Tracking and Reconstruction of 3D Human Motion in Monocular Video Sequences , 2001 .

[14]  Takeo Kanade,et al.  Shape-from-silhouette of articulated objects and its use for human body kinematics estimation and motion capture , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[15]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..