Title :
Modeling View and Posture Manifolds for Tracking
Author :
Lee, Chan-Su ; Elgammal, Ahmed
Author_Institution :
Rutgers Univ. Piscataway, Piscataway
Abstract :
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.
Keywords :
image motion analysis; learning (artificial intelligence); pose estimation; tracking; 3D configuration tracking; body configuration manifold; complex motion pose estimation; learning procedure; multiple continuous manifolds; person shape manifold modeling; posture manifolds; visual manifold; Biological system modeling; Cameras; Computer science; Humans; Kinematics; Lighting; Search problems; Shape; Solid modeling; Tracking;
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2007.4409030