Learning in graphical models
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Reconstruction of articulated objects from point correspondences in a single uncalibrated image
Computer Vision and Image Understanding
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating Human Body Configurations Using Shape Context Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
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)
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Sequential mean field variational analysis of structured deformable shapes
Computer Vision and Image Understanding
Bayesian network based human pose estimation
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Fast nonparametric belief propagation for real-time stereo articulated body tracking
Computer Vision and Image Understanding
Efficient duration and hierarchical modeling for human activity recognition
Artificial Intelligence
Sequential mean field variational analysis of structured deformable shapes
Computer Vision and Image Understanding
Human pose estimation using a mixture of Gaussians based image modeling
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
A coarse-and-fine Bayesian belief propagation for correspondence problems in computer vision
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Estimating 3D pose via stochastic search and expectation maximization
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
Monocular human pose tracking using multi frame part dynamics
WMVC'09 Proceedings of the 2009 international conference on Motion and video computing
Combination of annealing particle filter and belief propagation for 3D upper body tracking
Applied Bionics and Biomechanics - Personal Care Robotics
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We present an algorithm for automatic inference of human upper body motion. A graph model is proposed for inferring human motion, and motion inference is posed as a mapping problem between state nodes in the graph model and features in image patches. Belief propagation is utilized for Bayesian inference in this graph. A multiple-frame inference model/algorithm is proposed to combine both structural and temporal constraints in human motion. We also present a method for capturing constraints of human body configuration under different view angles. The algorithm is applied in a prototype system that can automatically label upper body motion from videos, without manual initialization of body parts.