TY - GEN
T1 - A person re-identification algorithm by using region-based feature selection and feature fusion
AU - Geng, Yanbing
AU - Hu, Hai Miao
AU - Zheng, Jin
AU - Li, Bo
PY - 2013
Y1 - 2013
N2 - In outdoor surveillance, person appearances captured by different cameras have obvious variations due to different poses and viewpoints, which affect the accuracy of person re-identification. In this paper, a person re-identification algorithm by using region-based feature selection and future fusion is proposed to divide one body into the upper region and the lower region. According to their different characteristics, each region adopts different kinds of features, which can efficiently reduce the negative impact from different poses and viewpoints. Moreover, since different features of one region may have different intrinsic meanings, during the feature fusion, different features of one region are separately represented instead of being comprehensively processed. The proposed feature fusion can make full use of the salience of different features. The experimental results demonstrate that the proposed algorithm improves the accuracy of person re-identification compared with the state of the art.
AB - In outdoor surveillance, person appearances captured by different cameras have obvious variations due to different poses and viewpoints, which affect the accuracy of person re-identification. In this paper, a person re-identification algorithm by using region-based feature selection and future fusion is proposed to divide one body into the upper region and the lower region. According to their different characteristics, each region adopts different kinds of features, which can efficiently reduce the negative impact from different poses and viewpoints. Moreover, since different features of one region may have different intrinsic meanings, during the feature fusion, different features of one region are separately represented instead of being comprehensively processed. The proposed feature fusion can make full use of the salience of different features. The experimental results demonstrate that the proposed algorithm improves the accuracy of person re-identification compared with the state of the art.
KW - feature fusion
KW - feature selection
KW - outdoor surveillance
KW - person re-identification
KW - region-based
UR - https://www.scopus.com/pages/publications/84897766576
U2 - 10.1109/ICIP.2013.6738693
DO - 10.1109/ICIP.2013.6738693
M3 - 会议稿件
AN - SCOPUS:84897766576
SN - 9781479923410
T3 - 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
SP - 3363
EP - 3366
BT - 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
PB - IEEE Computer Society
T2 - 2013 20th IEEE International Conference on Image Processing, ICIP 2013
Y2 - 15 September 2013 through 18 September 2013
ER -