TY - JOUR
T1 - RGB-T image analysis technology and application
T2 - A survey
AU - Song, Kechen
AU - Zhao, Ying
AU - Huang, Liming
AU - Yan, Yunhui
AU - Meng, Qinggang
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/4
Y1 - 2023/4
N2 - 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.
AB - 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.
KW - Image fusion
KW - Object tracking
KW - Pedestrian detection
KW - Person re-identification
KW - RGB-T images
KW - Salient object detection
KW - Visible-thermal
UR - http://www.scopus.com/inward/record.url?scp=85147848947&partnerID=8YFLogxK
U2 - 10.1016/j.engappai.2023.105919
DO - 10.1016/j.engappai.2023.105919
M3 - Short survey
AN - SCOPUS:85147848947
SN - 0952-1976
VL - 120
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
M1 - 105919
ER -