沈阳航空航天大学学报2025，Vol.42Issue(3)：51-57,7.DOI:10.3969/j.issn.2095-1248.2025.03.007
基于特征融合的视频行人重识别算法
Video person re-identification algorithm based on feature fusion
摘要
Abstract
Video person re-identification is a technology for identifying specific person in a multi-camera surveillance network.Compared to the methods based on single-frame images,this type of algorithms can provide more person information,but it also has issues such as model complexity and misalignment in constructing features.To address those issues,a feature fusion-based video person re-identification algorithm was proposed.The proposed algorithm included a global branch and a local branch with spatial transformation.The global branch extracted the global features of person,capturing coarse-grained information and overall contextual information of the person.The local branch with spatial transformation integrated a spatial transformation matrix into the local branch to learn discriminative local regional features and alleviating the issue of feature misalignment.By utilizing a multi-branch structure,the algorithm fused local and global features and aggregated features through temporal average pooling to enhance the diversity of features and improve the robustness of the model.Finally,the model was trained using cross-entropy and a soft boundary triplet loss.The test results on the Mars and DukeMTMC-Video datasets have verified the feasibility of the proposed algorithm.Specifically,the Mars dataset achieves mAP and Rank-1 accuracies of 82.25%and 89.76%respectively,demonstrating excellent practicality.关键词
行人重识别/深度学习/多损失函数/多分支结构/特征融合Key words
person re-identification/deep learning/multi-loss function/multi-branch structure/feature fusion分类
信息技术与安全科学引用本文复制引用
宋京浩,姬晓飞,孙英超,王竹筠..基于特征融合的视频行人重识别算法[J].沈阳航空航天大学学报,2025,42(3):51-57,7.基金项目
国家自然科学基金(项目编号:62003224). （项目编号:62003224）
