Simulating humans: computer graphics animation and control
Simulating humans: computer graphics animation and control
Video based human animation technique
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Reconstruction of articulated objects from point correspondences in a single uncalibrated image
Computer Vision and Image Understanding
Probabilistic Tracking with Exemplars in a Metric Space
International Journal of Computer Vision - Marr Prize Special Issue
Building Roadmaps of Local Minima of Visual Models
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
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
Inferring 3D Structure with a Statistical Image-Based Shape Model
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
On the improvement of anthropometry and pose estimation from a single uncalibrated image
Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
ACM Computing Surveys (CSUR)
Kinematic jump processes for monocular 3D human tracking
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Adding image constraints to inverse kinematics for human motion capture
EURASIP Journal on Advances in Signal Processing - Image processing and analysis in biomechanics
Model-based 3D tracking of an articulated hand from single depth images
Pattern Recognition Letters
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We present a method to reconstruct human motion pose from uncalibrated monocular video sequences based on the morphing appearance model matching. The human pose estimation is made by integrated human joint tracking with pose reconstruction in depth-first order. Firstly, the Euler angles of joint are estimated by inverse kinematics based on human skeleton constrain. Then, the coordinates of pixels in the body segments in the scene are determined by forward kinematics, by projecting these pixels in the scene onto the image plane under the assumption of perspective projection to obtain the region of morphing appearance model in the image. Finally, the human motion pose can be reconstructed by histogram matching. The experimental results show that this method can obtain favorable reconstruction results on a number of complex human motion sequences.