Style adaptive contour tracking of human gait using explicit manifold models

Title
Style adaptive contour tracking of human gait using explicit manifold models
Author(s)
이찬수아메드 엘가멜[아메드 엘가멜]
Keywords
NONLINEAR DIMENSIONALITY REDUCTION; HUMAN MOTION CAPTURE; SHAPE PRIORS
Issue Date
201205
Publisher
SPRINGER
Citation
MACHINE VISION AND APPLICATIONS, v.23, no.3, pp.461 - 478
Abstract
In the domain of human motion analysis, the observed contours of the body contain rich information about the body configuration, the motion performed, the person's identity, and even the emotional states of the person. In this paper, we introduce a framework for Bayesian tracking of the dynamic contours of the articulated human motion. We propose a factorized generative model for walking shape contour sequences that separates the dynamic deformation due to a motion, from the static variability due to the appearance of the person performing that motion. This results in an efficient tracking of gait sequence with a low-dimensional representation of body configuration and simultaneous adaptation to highly nonlinear static and dynamic shape deformations. Experimental results using the CMU Mobo, the University of Southampton (UoS), and M. Black's walking sequence, show accurate contour tracking of a person walking by dynamic body configuration estimation on a low-dimensional manifold space and personal style estimation to fit the contour to the individual characteristics. In addition, the estimated shape style provides a good descriptors for human identification from gait.
URI
http://hdl.handle.net/YU.REPOSITORY/28288http://dx.doi.org/10.1007/s00138-010-0303-y
ISSN
0932-8092
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