The problem described in this paper consists in reidentifying moving people in different sites with nonoverlapping views. Our proposed framework relies on a spectral analysis of the appearance-based signatures extracted from a detected person in each sequence. First, we propose a new feature called “color-position” histogram combined with several illuminant invariant methods in order to characterize extracted silhouettes in static images. Then, a graph-based approach that characterizes the most useful information of video sequences is presented to compare sequences, two by two, and to make the final decision of re-identification. The global system is tested on a real and difficult data set composed of 40 individuals recorded in very different environments: indoors near windows and outdoors with very different lighting conditions. The experimental results show that our approach provides reliable results and is promising with regard to surveillance security applications.
['Dung Nghi Truong Cong', 'Louahdi Khoudour', 'Catherine Achard', 'Philippe Phothisane']
People Re-Identification by Means of a Camera Network Using a Graph-Based Approach.