[2Yin5] インタラクティブ2

[2Yin5-13] Person Re-identification based on Shape and Texture Feature Reconstruction

〇Yuki Murata¹, Masayasu Atsumi¹ (1.Soka University Graduate School of Science and Engineering)

Keywords:Person Re-identification, Shape Feature Reconstruction, Texture Feature Reconstruction

In the field of person re-identification, it is necessary to deal with various poses and clothing changes to identify the same person from multiple camera images. However, existing deep learning methods, which are strongly affected by appearance of person images, have problems in extracting person features invariant to poses and clothing. To solve this problem, we propose models that jointly learn networks for reconstructing shape and texture features used in 3DCG person synthesis in addition to a person feature extraction network for person re-identification. The proposed model has an OSNet as the backbone and consists of a shape feature reconstruction module, a texture reconstruction module, and a person re-identification module. We evaluate the robustness of the proposed model to changes by using the LTCC dataset, where changes in clothing are taken into account, and the reconstructed Market-1501 dataset to take into account changes in poses.