Equal-distance sampling of superellipse models
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Model-Based Estimation of 3D Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Body Model Acquisition and Tracking Using Voxel Data
International Journal of Computer Vision
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)
Model-Based Multiple View Reconstruction of People
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Improved Adaptive Gaussian Mixture Model for Background Subtraction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
Shape-From-Silhouette Across Time Part I: Theory and Algorithms
International Journal of Computer Vision
International Journal of Computer Vision
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model-Based Approach for Estimating Human 3D Poses in Static Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering 3D Human Body Configurations Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Adaptive Appearance Model Approach for Model-based Articulated Object Tracking
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
Tracking People by Learning Their Appearance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast stochastic optimization for articulated structure tracking
Image and Vision Computing
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
Viewpoint invariant exemplar-based 3D human tracking
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Markerless tracking of complex human motions from multiple views
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Multi-cue Pedestrian Detection and Tracking from a Moving Vehicle
International Journal of Computer Vision
A Bayesian, Exemplar-Based Approach to Hierarchical Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Motion Tracking with a Kinematic Parameterization of Extremal Contours
International Journal of Computer Vision
Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts
International Journal of Computer Vision
Human Pose Tracking in Monocular Sequence Using Multilevel Structured Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Single-Frame 3D Human Pose Recovery from Multiple Views
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Multicamera tracking of articulated human motion using shape and motion cues
IEEE Transactions on Image Processing
3D Human Motion Tracking with a Coordinated Mixture of Factor Analyzers
International Journal of Computer Vision
Twin Gaussian Processes for Structured Prediction
International Journal of Computer Vision
A Study of Parts-Based Object Class Detection Using Complete Graphs
International Journal of Computer Vision
Guest Editorial: State of the Art in Image- and Video-Based Human Pose and Motion Estimation
International Journal of Computer Vision
International Journal of Computer Vision
Coupled Visual and Kinematic Manifold Models for Tracking
International Journal of Computer Vision
Optimization and Filtering for Human Motion Capture
International Journal of Computer Vision
A Study on Smoothing for Particle-Filtered 3D Human Body Tracking
International Journal of Computer Vision
Physics-Based Person Tracking Using the Anthropomorphic Walker
International Journal of Computer Vision
Part template: 3D representation for multiview human pose estimation
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 introduce a framework for unconstrained 3D human upper body pose estimation from multiple camera views in complex environment. Its main novelty lies in the integration of three components: single-frame pose recovery, temporal integration and model texture adaptation. Single-frame pose recovery consists of a hypothesis generation stage, in which candidate 3D poses are generated, based on probabilistic hierarchical shape matching in each camera view. In the subsequent hypothesis verification stage, the candidate 3D poses are re-projected into the other camera views and ranked according to a multi-view likelihood measure. Temporal integration consists of computing K-best trajectories combining a motion model and observations in a Viterbi-style maximum-likelihood approach. Poses that lie on the best trajectories are used to generate and adapt a texture model, which in turn enriches the shape likelihood measure used for pose recovery. The multiple trajectory hypotheses are used to generate pose predictions, augmenting the 3D pose candidates generated at the next time step.We demonstrate that our approach outperforms the state-of-the-art in experiments with large and challenging real-world data from an outdoor setting.