期刊
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
卷 120, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2023.105919
关键词
RGB-T images; Visible-thermal; Image fusion; Salient object detection; Pedestrian detection; Object tracking; Person re-identification
RGB-T image analysis has gained wide attention and made significant research progress in various applications. This paper provides a comprehensive review of the technology and applications in the fields of image fusion, salient object detection, semantic segmentation, pedestrian detection, object tracking, and person re-identification. It extensively reviews more than 400 papers across over 10 different application tasks, analyzing various methods and presenting the performance of state-of-the-art techniques. Additionally, it offers an in-depth analysis of challenges and potential technical improvements for future RGB-T image analysis.
RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent years. In the past decade, it has received wide attention and made a lot of important research progress in many applications. This paper provides a comprehensive review of RGB-T image analysis technology and application, including several hot fields: image fusion, salient object detection, semantic segmentation, pedestrian detection, object tracking, and person re-identification. The first two belong to the preprocessing technology for many computer vision tasks, and the rest belong to the application direction. This paper extensively reviews 400+ papers spanning more than 10 different application tasks. Furthermore, for each specific task, this paper comprehensively analyzes the various methods and presents the performance of the state-of-the-art methods. This paper also makes an in-deep analysis of challenges for RGB-T image analysis as well as some potential technical improvements in the future.
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