Matching Groups of People by Covariance Descriptor

In this paper, we present a new solution to the problem of matching groups of people across multiple non-overlapping cameras. Similar to the problem of matching individuals across cameras, matching groups of people also faces challenges such as variations of illumination conditions, poses and camera...

Full description

Saved in:
Bibliographic Details
Published in2010 20th International Conference on Pattern Recognition pp. 2744 - 2747
Main Authors Yinghao Cai, Takala, V, Pietikainen, M
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.08.2010
Subjects
Cameras
Character recognition
Histograms
Image color analysis
Legged locomotion
Lighting
Pixel
Online AccessGet full text

Cover

More Information
Summary:In this paper, we present a new solution to the problem of matching groups of people across multiple non-overlapping cameras. Similar to the problem of matching individuals across cameras, matching groups of people also faces challenges such as variations of illumination conditions, poses and camera parameters. Moreover, people often swap their positions while walking in a group. In this paper, we propose to use covariance descriptor in appearance matching of group images. Covariance descriptor is shown to be a discriminative descriptor which captures both appearance and statistical properties of image regions. Furthermore, it presents a natural way of combining multiple heterogeneous features together with a relatively low dimensionality. Experimental results on two different datasets demonstrate the effectiveness of the proposed method.
ISBN:1424475422
9781424475421
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2010.672