Specialized mappings and the estimation of human body pose from a single image
HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
Inferring 3D Structure with a Statistical Image-Based Shape Model
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Bayesian Approach to Background Modeling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Monitoring of Vulnerable People in Home Environment
ICOST '08 Proceedings of the 6th international conference on Smart Homes and Health Telematics
Estimation of human orientation in images captured with a range camera
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Combination of annealing particle filter and belief propagation for 3D upper body tracking
Applied Bionics and Biomechanics - Personal Care Robotics
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This paper deals with human body pose recovery through a multicamera system, which is a key task in monitoring of human activity. The proposed algorithm reconstructs the 3D visual hull of the observed body and characterizes its shape with a new 3D shape descriptor. The body pose is then infered through an original two-stage regression process. As the learning step is independant of the camera configuration, the resulting system is easy to set up. This solution is evaluated on synthetic scenes and promising results on real images are also presented.