Local Heterogeneous Features for Person Re-Identification in Harsh Environments

Local Heterogeneous Features for Person Re-Identification in Harsh Environments

Local features could learn semantic information for pedestrian images and they are very important for person re-identification (Re-ID) in harsh environments. However, most approaches only optimize one kind of local feature, which results in incomplete local features. In this paper, we propose Local...

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Bibliographic Details
Main Authors: Haijia Zhang, Tongzhen Si, Zhong Zhang, Ronghua Zhang, Hao Ma, Shuang Liu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Person re-identification
local heterogeneous features
harsh environments
Online Access:https://ieeexplore.ieee.org/document/9084088/

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