Markerless human motion tracking with a flexible model and appearance learning

Authors:
Florian Hecht;Pedram Azad;Rüdiger Dillmann
Affiliations:
University of Karlsruhe, Germany;Institute for Technical Informatics, University of Karlsruhe, Germany;Institute for Technical Informatics, University of Karlsruhe, Germany
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

Citing 5
Cited 1

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MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Real-Time Markerless Human Body Tracking Using Colored Voxels and 3-D Blobs

ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Markerless Motion Capture using Multiple Cameras

CVIIE '05 Proceedings of the Computer Vision for Interactive and Intelligent Environment
Markerless monocular motion capture using image features and physical constraints

CGI '05 Proceedings of the Computer Graphics International 2005
Shape-from-silhouette of articulated objects and its use for human body kinematics estimation and motion capture

CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition

Interactive imitation learning of object movement skills

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Abstract

A new approach to the 3D human motion tracking problem is proposed, which combines several particle filters with a physical simulation of a flexible body model. The flexible body model allows the partitioning of the state space of the human model into much smaller subsets, while finding a solution considering all the partial results of the particle filters. The flexible model also creates the necessary interaction between the different particle filters and allows effective semi-hierarchical tracking of the human body. The physical simulation does not require inverse kinematics calculations and is hence fast and easy to implement. Furthermore the system also builds an appearance model on-the-fly which allows it to work without a foreground segmentation. The system is able to start tracking automatically with a convenient initialization procedure. The implementation runs with 10 Hz on a regular PC using a stereo camera and is hence suitable for Human-Robot Interaction applications.