In this paper we consider modeling data lying on multiple continuous manifolds. In particular, we model the shape manifold of a person performing a motion observed from different view points along a view circle at fixed camera height. We introduce a model that ties together the body configuration (kinematics) manifold and the visual manifold (observations) in a way that facilitates tracking the 3D configuration with continuous relative view variability. The model exploits the low dimensionality nature of both the body configuration manifold and the view manifold where each of them are represented separately. 1
We propose a novel visual tracking scheme that exploits boththe geometrical structure of Grassmann m...
We propose a 2D model-based approach for tracking human body parts during articulated motion. A huma...
We propose a novel kinematic prior for 3D human pose tracking that allows predicting the position in...
This paper proposes a new method for model-based tracking of a human body in 3D motion from multiple...
Modeling the dynamic shape and appearance of articulated moving objects is essential for human motio...
This paper proposes a clustered exemplar-based model for performing viewpoint invariant tracking of ...
Many existing systems for human body tracking are based on dynamic model-based tracking that is driv...
We study the task to infer and to track the viewpoint onto a 3D rigid object by observing its image ...
Many existing systems for human body tracking are based on dynamic model-based tracking that is driv...
We present a new method for the 3D model-based tracking of human body parts. To mitigate the difficu...
Action recognition by the brain is thought to combine the recognition of body configurations with so...
Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem....
This paper presents a robust computational framework for monocular 3D tracking of human movement. Th...
Computer vision-based markerless human body tracking plays an important role in e.g. surveillance an...
A major challenge in applying Bayesian tracking methods for tracking 3D human body pose is the high ...
We propose a novel visual tracking scheme that exploits boththe geometrical structure of Grassmann m...
We propose a 2D model-based approach for tracking human body parts during articulated motion. A huma...
We propose a novel kinematic prior for 3D human pose tracking that allows predicting the position in...
This paper proposes a new method for model-based tracking of a human body in 3D motion from multiple...
Modeling the dynamic shape and appearance of articulated moving objects is essential for human motio...
This paper proposes a clustered exemplar-based model for performing viewpoint invariant tracking of ...
Many existing systems for human body tracking are based on dynamic model-based tracking that is driv...
We study the task to infer and to track the viewpoint onto a 3D rigid object by observing its image ...
Many existing systems for human body tracking are based on dynamic model-based tracking that is driv...
We present a new method for the 3D model-based tracking of human body parts. To mitigate the difficu...
Action recognition by the brain is thought to combine the recognition of body configurations with so...
Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem....
This paper presents a robust computational framework for monocular 3D tracking of human movement. Th...
Computer vision-based markerless human body tracking plays an important role in e.g. surveillance an...
A major challenge in applying Bayesian tracking methods for tracking 3D human body pose is the high ...
We propose a novel visual tracking scheme that exploits boththe geometrical structure of Grassmann m...
We propose a 2D model-based approach for tracking human body parts during articulated motion. A huma...
We propose a novel kinematic prior for 3D human pose tracking that allows predicting the position in...