Proceedings of the 18th annual conference on Computer graphics and interactive techniques
The background primal sketch: an approach for tracking moving objects
Machine Vision and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonrigid motion analysis: articulated and elastic motion
Computer Vision and Image Understanding
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Real-time inverse kinematics techniques for anthropomorphic limbs
Graphical Models and Image Processing
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Convolution surfaces for line skeletons with polynomial weight distributions
Journal of Graphics Tools
Motion Estimation of Articulated Objects from Perspective Views
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
3-D model-based tracking of humans in action: a multi-view approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Cardboard People: A Parameterized Model of Articulated Image Motion
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Automated Detection of Human for Visual Surveillance System
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Pose Estimation of a 2-D Articulated Object from Its Silhouette Using a GA
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Continuous capture of skin deformation
ACM SIGGRAPH 2003 Papers
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In this paper we present a novel class of human model described by convolution surface attached to articulated kinematics skeletons. The human pose can be estimated from silhouette in monocular images. The contribution of this paper consists of three points: First, human model of convolution surface is presented and its shape is deformable when changing polynomial parameters and radius parameters. Second, convolution surface and curve correspondence theorem is presented to give a map between 3D pose and 2D contour. Third, we model the human silhouette with convolution curve in order to estimate joint parameters from monocular images and we also give an effective constraint function. Evaluation of this approach is performed on some video frames about a walking man. The experiment result shows that our method works well without self-occlusion.