https://scholars.lib.ntu.edu.tw/handle/123456789/581485
標題: | Illumination-Adaptive Person Re-Identification | 作者: | Zeng Z Wang Z Wang Z Zheng Y Chuang Y.-Y Satoh S. YUNG-YU CHUANG |
關鍵字: | Multimedia systems; Signal processing; Identity information; Illumination conditions; Illumination variation; Person re identifications; Real-world image; Simulated datasets; Large dataset | 公開日期: | 2020 | 卷: | 22 | 期: | 12 | 起(迄)頁: | 3064-3074 | 來源出版物: | IEEE Transactions on Multimedia | 摘要: | Most person re-identification (ReID) approaches assume that person images are captured under relatively similar illumination conditions. In reality, long-term person retrieval is common, and person images are often captured under different illumination conditions at different times across a day. In this situation, the performances of existing ReID models often degrade dramatically. This paper addresses the ReID problem with illumination variations and names it as Illumination-Adaptive Person Re-identification (IA-ReID). We propose an Illumination-Identity Disentanglement (IID) network to dispel different scales of illuminations away while preserving individuals' identity information. To demonstrate the illumination issue and to evaluate our model, we construct two large-scale simulated datasets with a wide range of illumination variations. Experimental results on the simulated datasets and real-world images demonstrate the effectiveness of the proposed framework. ? 1999-2012 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084918274&doi=10.1109%2fTMM.2020.2969782&partnerID=40&md5=18843e630f60a527985365e8238641f5 https://scholars.lib.ntu.edu.tw/handle/123456789/581485 |
ISSN: | 15209210 | DOI: | 10.1109/TMM.2020.2969782 |
顯示於: | 資訊工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。