Singularity analysis for articulated object tracking

We analyze the use of kinematic constraints for articulated object tracking. Conditions for the occurrence of singularities in 3-D models are presented and their effects on tracking are characterized We describe a novel 2-D Scaled Prismatic Model (SPM) for figure registration. In contrast to 3-D kinematic models, the SPM has fewer singularity problems and does not require detailed knowledge of the 3-D kinematics. We fully characterize the singularities in the SPM and illustrate tracking through singularities using synthetic and real examples with 3-D and 2-D models. Our results demonstrate the significant benefits of the SPM in tracking with a single source of video.

[1]  J. O'Rourke,et al.  Model-based image analysis of human motion using constraint propagation , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  David C. Hogg Model-based vision: a program to see a walking person , 1983, Image Vis. Comput..

[3]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[4]  D. Pai Singularity, uncertainty and compliance of robot manipulators , 1988 .

[5]  Mark W. Spong,et al.  Robot dynamics and control , 1989 .

[6]  Yoshihiko Nakamura,et al.  Advanced robotics - redundancy and optimization , 1990 .

[7]  Masanobu Yamamoto,et al.  Human motion analysis based on a robot arm model , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Alex Pentland,et al.  Recovery of Nonrigid Motion and Structure , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Takeo Kanade,et al.  Visual Tracking of High DOF Articulated Structures: an Application to Human Hand Tracking , 1994, ECCV.

[10]  James M. Rehg Visual analysis of high DOF articulated objects with application to hand tracking , 1995 .

[11]  Takeo Kanade,et al.  Model-based tracking of self-occluding articulated objects , 1995, Proceedings of IEEE International Conference on Computer Vision.

[12]  Ioannis A. Kakadiaris,et al.  Model-based estimation of 3D human motion with occlusion based on active multi-viewpoint selection , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Michael J. Black,et al.  Cardboard people: a parameterized model of articulated image motion , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[14]  Larry S. Davis,et al.  3-D model-based tracking of humans in action: a multi-view approach , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[15]  Rajeev Sharma,et al.  Motion perceptibility and its application to active vision-based servo control , 1997, IEEE Trans. Robotics Autom..

[16]  James M. Rehg,et al.  TM Singularities in Articulated Object Tracking with 2-D and 3-D Models , 1997 .

[17]  George Leitmann,et al.  Dynamics and Control , 2020, Fundamentals of Robotics.

[18]  Ioannis A. Kakadiaris,et al.  Model-Based Estimation of 3D Human Motion , 2000, IEEE Trans. Pattern Anal. Mach. Intell..