DocumentCode
2461193
Title
Modeling View and Posture Manifolds for Tracking
Author
Lee, Chan-Su ; Elgammal, Ahmed
Author_Institution
Rutgers Univ. Piscataway, Piscataway
fYear
2007
fDate
14-21 Oct. 2007
Firstpage
1
Lastpage
8
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location
Rio de Janeiro
ISSN
1550-5499
Print_ISBN
978-1-4244-1630-1
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2007.4409030
Filename
4409030
Link To Document