Dual Channel Gradient feature for person re-identification

Recently, several effective features were proposed for person re-identification, such as Weight Histograms of Overlapping Stripes (WHOS) and Local Maximal Occurrence (LOMO), but it still need to explore new effective feature to improve the precision for person re-identification. So, in this paper, w...

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Bibliographic Details
Main Authors: Jiabao Wang, Yang Li, Hang Li, Yulong Xu, Zhuang Miao, Gengning Zhang
Format: Conference Proceeding
Language:English
Subjects:
Cameras
dual channel feature
Feature extraction
feature fusion
Histograms
Image color analysis
Kernel
Measurement
person re-identification
Training
Online Access:Request full text
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Summary:Recently, several effective features were proposed for person re-identification, such as Weight Histograms of Overlapping Stripes (WHOS) and Local Maximal Occurrence (LOMO), but it still need to explore new effective feature to improve the precision for person re-identification. So, in this paper, we proposed a new Dual Channel Gradient feature, which can be fused with WHOS and LOMO by directly concatenating the normalized histograms. Experimental results showed that the fused feature can achieve the state-of-the-art accuracy, on four public datasets with two different metric learning methods.
ISSN:2472-7628
DOI:10.1109/WCSP.2016.7752447