RGB thermal(RGBT)visual tracking is an emerging hot research topic on visual tracking,it fuses visible and thermal infrared multimodal image information,and the reasonable fusion of complementary information of visible and thermal infrared images can improve the performance and robustness of trackers.Artificial intelligence technology has promoted the development of RGBT multimodal visual tracking,and deep learning technology gradually replaces traditional target tracking methods,with more advantages of accuracy and speed.Comprehensively overview the development of RGBT multimodal visual tracking,summarize and discuss relat-ed algorithms,specifically including correlation filtering-based methods and deep learning-based methods,review the development his-tory of RGBT multimodal visual tracking datasets,introduce algorithm performance evaluation indexes,analyze the performance of different algorithms on evaluation datasets,and look forward to the future research trends of RGBT multimodal visual tracking meth-ods.This paper aims to provide a comprehensive overview and reference for related researchers to promote research and development in RGBT multimodal vision tracking fields.
万方数据
维普
