@Article{jnm.2023.038580,
AUTHOR = {Yinyin Zhang},
TITLE = {Review of Visible-Infrared Cross-Modality Person Re-Identification},
JOURNAL = {Journal of New Media},
VOLUME = {5},
YEAR = {2023},
NUMBER = {1},
PAGES = {23--31},
URL = {http://www.techscience.com/JNM/v5n1/53131},
ISSN = {2579-0129},
ABSTRACT = {Person re-identification (ReID) is a sub-problem under image retrieval. It is a technology that uses computer vision to identify a specific pedestrian in a collection of pictures or videos. The pedestrian image under cross-device is taken from a monitored pedestrian image. At present, most ReID methods deal with the matching between visible and visible images, but with the continuous improvement of security monitoring system, more and more infrared cameras are used to monitor at night or in dim light. Due to the image differences between infrared camera and RGB camera, there is a huge visual difference between cross-modality images, so the traditional ReID method is difficult to apply in this scene. In view of this situation, studying the pedestrian matching between visible and infrared modalities is particularly crucial. Visible-infrared person re-identification (VI-ReID) was first proposed in 2017, and then attracted more and more attention, and many advanced methods emerged.},
DOI = {10.32604/jnm.2023.038580}
}