Learning flexible models from image sequences
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Model-Based Estimation of 3D Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Probabilistic Exclusion Principle for Tracking Multiple Objects
International Journal of Computer Vision
Reconstruction of articulated objects from point correspondences in a single uncalibrated image
Computer Vision and Image Understanding
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Fusion of Multiple Tracking Algorithms for Robust People Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
A Novel Approach to Generate Multiple Shape Models for Tracking Applications
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Color active shape models for tracking non-rigid objects
Pattern Recognition Letters - Special issue: Colour image processing and analysis
Wormholes in Shape Space: Tracking through Discontinuous Changes in Shape
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Inferring 3D Structure with a Statistical Image-Based Shape Model
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
2D Silhouette and 3D Skeletal Models for Human Detection and Tracking
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Priors for People Tracking from Small Training Sets
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Bayesian Body Localization Using Mixture of Nonlinear Shape Models
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Matching Shape Sequences in Video with Applications in Human Movement Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering 3D Human Pose from Monocular 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
Tracking People by Learning Their Appearance
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Human body pose detection using Bayesian spatio-temporal templates
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
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Kinematic jump processes for monocular 3D human tracking
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Human figure segmentation using independent component analysis
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Bio-inspired Connectionist Architecture for Visual Detection and Refinement of Shapes
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Unsupervised human motion analysis using automatic label trees
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Visual affect recognition
Computer Vision and Image Understanding
Fast Human Pose Detection Using Randomized Hierarchical Cascades of Rejectors
International Journal of Computer Vision
Comparing evolutionary algorithms and particle filters for Markerless Human Motion Capture
Applied Soft Computing
Computer Vision and Image Understanding
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This paper addresses the pose recovery problem of a particular articulated object: the human body. In this model-based approach, the 2D-shape is associated to the corresponding stick figure allowing the joint segmentation and pose recovery of the subject observed in the scene. The main disadvantage of 2D-models is their restriction to the viewpoint. To cope with this limitation, local spatio-temporal 2D-models corresponding to many views of the same sequences are trained, concatenated and sorted in a global framework. Temporal and spatial constraints are then considered to build the probabilistic transition matrix (PTM) that gives a frame to frame estimation of the most probable local models to use during the fitting procedure, thus limiting the feature space. This approach takes advantage of 3D information avoiding the use of a complex 3D human model. The experiments carried out on both indoor and outdoor sequences have demonstrated the ability of this approach to adequately segment pedestrians and estimate their poses independently of the direction of motion during the sequence.