中圖分類號： TP391
文獻標識碼： A
DOI： 10.19358/j.issn.2096-5133.2021.06.006
引用格式： 彭玉青，李偉，郭永芳. 融合外觀特征的行人重識別方法[J].信息技術與網絡安全，2021，40(6)：33-37，49.

Person re-identification incorporating appearance feature

Abstract： Aiming at the problem of low recognition rate caused by pose, viewpoint and occlusion in person re-identification, a method incorporating appearance feature is proposed. The method designs two network branches to extract global feature and local feature of pedestrians respectively, and the two are fused to obtain the appearance features of pedestrians. Simultaneously the model is optimized by a multi-task learning strategy for both network branches through combining classification loss and metric learning loss. In addition, the model combines with random erasing algorithm to add noise to the dataset for enhancing the robustness of the model. The experimental results show that the proposed method incorporating appearance feature greatly improves the accuracy of person re-ID, with rank-1 reaching 92.82% and mAP reaching 80.51% on the Market1501 dataset, and rank-1 reaching 85.06% and mAP reaching 72.72% on the DukeMTMC-reID dataset.

Key words : person re-identification；feature incorporating；random erasing；multi-task learning