Coupled Visual and Kinematic Manifold Models for Tracking

Title
Coupled Visual and Kinematic Manifold Models for Tracking
Author(s)
이찬수A. Elgammal[A. Elgammal]
Keywords
NONLINEAR DIMENSIONALITY REDUCTION; 3D HUMAN MOTION; RECOGNITION; APPEARANCE; PROPAGATION; SHAPE
Issue Date
201003
Publisher
SPRINGER
Citation
INTERNATIONAL JOURNAL OF COMPUTER VISION, v.87, no.1-2, pp.118 - 139
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 viewpoints along a view circle at a fixed camera height. We introduce a model that ties together the body configuration (kinematics) manifold and visual (observations) manifold 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. The resulting representation is used for tracking complex motions within a Bayesian framework, in which the model provides a low-dimensional state representation as well as a constrained dynamic model for both body configuration and view variations. Experimental results estimating the 3D body posture from a single camera are presented for the HUMANEVA dataset and other complex motion video sequences.
URI
http://hdl.handle.net/YU.REPOSITORY/22742http://dx.doi.org/10.1007/s11263-009-0266-5
ISSN
0920-5691
Appears in Collections:
공과대학 > 전자공학과 > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE