Title :
Matching Groups of People by Covariance Descriptor
Author :
Cai, Yinghao ; Takala, Valtteri ; Pietikäinen, Matti
Author_Institution :
Dept. of Electr. & Inf. Eng., Univ. of Oulu, Oulu, Finland
Abstract :
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.
Keywords :
cameras; feature extraction; image matching; statistical analysis; covariance descriptor; illumination conditions; multiple heterogeneous features; multiple nonoverlapping cameras; statistical properties; Cameras; Character recognition; Histograms; Image color analysis; Legged locomotion; Lighting; Pixel;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.672