NDLI: Human identification using body prior and generalized EMD

Content Provider	IEEE Xplore Digital Library
Author	Lianyang Ma Xiaokang Yang Yi Xu Jun Zhu
Copyright Year	2011
Description	Author affiliation: Institute of Image Communication and Information Processing, Shanghai Key Labs of Digital Media Processing and Communication, Shanghai Jiao Tong University, Shanghai 200240, China (Lianyang Ma; Xiaokang Yang; Yi Xu; Jun Zhu)
Abstract	The general configuration of body is a valuable cue for human identification, which is ignored by the existing approaches. In this paper, we present an approach for human identification by using body prior and the generalized Earth Mover's Distance (EMD). The common knowledge that a pedestrian is composed of upper body and the lower one is employed as a body prior. To achieve more robust body segmentation, we pursue their boundary by inducing a logistic probability map, which is approximated based on minimizing its KL divergence to the posterior probability of the observed person image. Furthermore, we generalize EMD by assigning different weights to regions of body, which are learned through logistic regression to boost discriminative power for human identification. The experimental results show that both body prior and the generalized EMD facilitate performance on human identification.
Starting Page	1441
Ending Page	1444
File Size	658629
Page Count	4
File Format	PDF
ISBN	9781457713040
ISSN	15224880
e-ISBN	9781457713033
e-ISBN	9781457713026
DOI	10.1109/ICIP.2011.6115774
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-11
Publisher Place	Belgium
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Image segmentation Measurement Feature extraction Image color analysis Conferences human identification body prior EMD KL divergence learning weight
Content Type	Text
Resource Type	Article

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