Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (6A): 240800156-7.doi: 10.11896/jsjkx.240800156

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Pedestrian Re-identification Based on Spatial Transformation and Multi-scale Feature Fusion

JIN Lu, LIU Mingkun, ZHANG Chunhong, CHEN Kefei, LUO Yaqiong, LI Bo   

  1. School of Information Engineering,College of Arts and Sciences Kunming,Kunming 650031,China
  • Online:2025-06-16 Published:2025-06-12
  • About author:JIN Lu,born in 1992,master,assistant lecturer.His main research interest is computer vision.
    LIU Minkun,bornin 1959,postgra-duate,professor.His main research in-terest is computer technology.

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Abstract: A network combining spatial transformation and multiscale feature fusion is designed to address the issue of insufficiently representing pedestrian information due to misalignment of pedestrian spatial characteristics and occlusion factors.Firstly,a method for enhancing pedestrian retrieval is proposed,aiming to improve the network’s ability to recognize special samples.Secondly,a self-attention spatial transformation network is introduced to address the problem of inconsistent spatial semantic information in pedestrian image regions.Then,different scale features are extracted from the network,and fused separately based on the characteristics of each branch,incorporating coordinate attention and instance batch normalization.Finally,the features of different branches are fused to obtain highly representative fused features.Experiments on multiple datasets show that the proposed method outperforms existing methods in terms of re-identification performance.

Key words: Pedestrian re-identification, Spatial transformation, Feature fusion, Multiple scale, Side window filtering

CLC Number: 

  • TP391.41
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