Multi-Scale Occluded Person Re-Identification Guided by Key Fine-Grained Information

ZHOU Yu; ZHAO Xiaofeng; WANG Yi; SUN Yanjing; LI Song

doi:10.11999/JEIT230686

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ZHOU Yu, ZHAO Xiaofeng, WANG Yi, SUN Yanjing, LI Song. Multi-Scale Occluded Person Re-Identification Guided by Key Fine-Grained Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230686

Citation:

ZHOU Yu, ZHAO Xiaofeng, WANG Yi, SUN Yanjing, LI Song. Multi-Scale Occluded Person Re-Identification Guided by Key Fine-Grained Information[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT230686

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Multi-Scale Occluded Person Re-Identification Guided by Key Fine-Grained Information

doi: 10.11999/JEIT230686

ZHOU Yu^{1, 2},
ZHAO Xiaofeng¹,
WANG Yi^{1, 3},
SUN Yanjing^{1
,
,},
LI Song¹

1.
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China
2.
Xuzhou First Peoples Hospital, Xuzhou 221116, China
3.
Jiangsu Normal University Kewen College, Xuzhou 221132, China

Funds: The National Natural Science Foundation of China (62001475), The National Natural Science Foundation of Jiangsu Province(BK20200649)

Received Date: 2023-07-07
Rev Recd Date: 2024-01-19

Available Online: 2024-01-26

Abstract

Abstract

To reduce the influence of background and occlusion on the accuracy of pedestrian identity Re-IDentification (ReID) and make full use of the complementarity between fine-grained and coarse-grained information, a multi-scale occluded pedestrian ReID network guided by key fine-grained information is proposed. First, the image is divided into two types of overlapping patches with different sizes to better simulate the multi-scale characteristics of human observing images and the continuity characteristics of human observing adjacent regions, so a multi-scale recognition network containing both fine-grained and coarse-grained information extraction branches is constructed. Then, considering fine-grained information contains more details and there are similarities and differences between fine-grained and coarse-grained information, fine-grained attention module is further employed to realize the guide of the fine-grained branch to the coarse-grained branch. Among them, the fine-grained information is the key information retained after filtering out the interference information by the Interference Information Elimination (IIE) module. Finally, the key information related to pedestrian ReID is obtained by bivariate difference, and the prediction of pedestrian identity is realized by multi-dimensional joint supervision such as tags and features. Extensive experiments on several public pedestrian ReID databases prove the superiority of this algorithm and the effectiveness and necessity of each module.
- Occluded person ReID,
- Multi-scale,
- Fine-grained information,
- Coarse-grained information,
- Interference information elimination

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References(23)

References

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