Parameter-controlled volume thinning
CVGIP: Graphical Models and Image Processing
3D articulated models and multiview tracking with physical forces
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Human Body Model Acquisition and Tracking Using Voxel Data
International Journal of Computer Vision
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
Monocular Human Motion Capture with a Mixture of Regressors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Tracking People by Learning Their Appearance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
3D Skeleton-Based Body Pose Recovery
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Pose-Oblivious Shape Signature
IEEE Transactions on Visualization and Computer Graphics
Curve-Skeleton Properties, Applications, and Algorithms
IEEE Transactions on Visualization and Computer Graphics
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
Real-time 3-D human body tracking using learnt models of behaviour
Computer Vision and Image Understanding
Consistent mesh partitioning and skeletonisation using the shape diameter function
The Visual Computer: International Journal of Computer Graphics
Human Motion Tracking with a Kinematic Parameterization of Extremal Contours
International Journal of Computer Vision
Model based human motion tracking using probability evolutionary algorithm
Pattern Recognition Letters
Model Driven Segmentation of Articulating Humans in Laplacian Eigenspace
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Pose Tracking in Monocular Sequence Using Multilevel Structured Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust human tracking based on multi-cue integration and mean-shift
Pattern Recognition Letters
International Journal of Computer Vision
An Effective Method for Foreground Segmentation of Video
ICIG '09 Proceedings of the 2009 Fifth International Conference on Image and Graphics
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A new hierarchical method for markerless human pose estimation
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
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We present a system for human pose estimation by using a single frame and without making assumptions on temporal coherence. The system uses 3D voxel data reconstructed from multiple synchronized video streams as input, and computes, for each frame, a skeleton model which best fits the body pose. This system adopts a hierarchical approach where the head and torso locations are found first based on template fitting with their specific shapes and dimensions. It is followed by a limb detection procedure that estimates the pose parameters of four limbs. However, a problem generally faced with skeleton models is the means to find adequate measurements to fit the model. In this paper, voxel data, together with two novel local shape features, are used for this purpose. Experiments show that this system is robust to several perturbations associated with the input data, such as voxel reconstruction errors and complex poses with self-contact, and also allows unconstrained motions, such as fast or unpredictable movements.