TY - GEN
T1 - An ensemble color model for human re-identification
AU - Liu, Xiaokai
AU - Wang, Hongyu
AU - Wu, Yi
AU - Yang, Jimei
AU - Yang, Ming Hsuan
PY - 2015/2/19
Y1 - 2015/2/19
N2 - Appearance-based human re-identification is challenging due to different camera characteristics, varying lighting conditions, pose variations across camera views, etc. Recent studies have revealed that color information plays a critical role on performance. However, two problems remain unclear: (1) how do different color descriptors perform under the same scene in re-identification problem? and (2) how can we combine these descriptors without losing their invariance property and distinctiveness power? In this paper, we propose a novel ensemble model that combines different color descriptors in the decision level through metric learning. Experiments show that the proposed system significantly outperforms state-of-the-art algorithms on two challenging datasets (VIPeR and PRID 450S). We have improved the Rank 1 recognition rate on VIPeR dataset by 8.7%.
AB - Appearance-based human re-identification is challenging due to different camera characteristics, varying lighting conditions, pose variations across camera views, etc. Recent studies have revealed that color information plays a critical role on performance. However, two problems remain unclear: (1) how do different color descriptors perform under the same scene in re-identification problem? and (2) how can we combine these descriptors without losing their invariance property and distinctiveness power? In this paper, we propose a novel ensemble model that combines different color descriptors in the decision level through metric learning. Experiments show that the proposed system significantly outperforms state-of-the-art algorithms on two challenging datasets (VIPeR and PRID 450S). We have improved the Rank 1 recognition rate on VIPeR dataset by 8.7%.
UR - http://www.scopus.com/inward/record.url?scp=84925385115&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84925385115&partnerID=8YFLogxK
U2 - 10.1109/WACV.2015.120
DO - 10.1109/WACV.2015.120
M3 - Conference contribution
AN - SCOPUS:84925385115
T3 - Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015
SP - 868
EP - 875
BT - Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015
Y2 - 5 January 2015 through 9 January 2015
ER -