Model-Based Estimation of 3D Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction of articulated objects from point correspondences in a single uncalibrated image
Computer Vision and Image Understanding
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
Estimating Human Body Configurations Using Shape Context Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Evaluating Video-Based Motion Capture
CA '02 Proceedings of the Computer Animation
Model-based estimation of 3D human motion with occlusion based on active multi-viewpoint selection
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
A sketching interface for articulated figure animation
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pictorial Structures for Object Recognition
International Journal of Computer Vision
Learning silhouette features for control of human motion
ACM Transactions on Graphics (TOG)
Realistic Rendering and Animation of a Multi-Layered Human Body Model
IV '06 Proceedings of the conference on Information Visualization
A real-time model-based human motion tracking and analysis for human computer interface systems
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
VideoMocap: modeling physically realistic human motion from monocular video sequences
ACM SIGGRAPH 2010 papers
Video-based 3D motion capture through biped control
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Accurate 3D pose estimation from a single depth image
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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We propose a framework to reconstruct the 3D pose of a human for animation from a sequence of single-view video frames. The framework for pose construction starts with background estimation and the performer@?s silhouette is extracted using image subtraction for each frame. Then the body silhouettes are automatically labeled using a model-based approach. Finally, the 3D pose is constructed from the labeled human silhouette by assuming orthographic projection. The proposed approach does not require camera calibration. It assumes that the input video has a static background, it has no significant perspective effects, and the performer is in an upright position. The proposed approach requires minimal user interaction.