Person Re-identification Using Haar-based and DCD-based Signature
In many surveillance systems there is a requirement to determine whether a given person of interest has already been observed over a network of cameras. This paper presents two approaches for this person re-identification problem. In general the human appearance obtained in one camera is usually dif...
Saved in:
Published in | 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance pp. 1 - 8 |
---|---|
Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.08.2010
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | In many surveillance systems there is a requirement to determine whether a given person of interest has already been observed over a network of cameras. This paper presents two approaches for this person re-identification problem. In general the human appearance obtained in one camera is usually different from the ones obtained in another camera. In order to re-identify people the human signature should handle difference in illumination, pose and camera parameters. Our appearance models are based on hoar-like features and dominant color descriptors. The AdaBoost scheme is applied to both descriptors to achieve the most invariant and discriminative signature. The methods are evaluated using benchmark video sequences with different camera views where people are automatically detected using Histograms of Oriented Gradients (HOG). The reidentification performance is presented using the cumulative matching characteristic (CMC) curve. |
---|---|
ISBN: | 9781424483105 1424483107 |
DOI: | 10.1109/AVSS.2010.68 |