A Comprehensive Review of RGBT Tracking

RGBT tracking seeks to leverage both visible and thermal infrared images to enhance the robustness of target tracking. This method makes up for the limitations of single-sensor tracking. The RGB and thermal infrared images complement each other effectively, enabling the tracker to operate seamlessly in complex environments day and night. However, RGBT tracking still faces challenges, such as thermal crossover, occlusion (OCC), illumination changes, rapid target movement, and background clutter. These problems hinder the performance improvement of RGBT trackers. Researchers have proposed numerous RGBT tracking methods in response to these challenges over time. This article aims to comprehensively review and summarize the latest research progress in RGBT tracking. First, we categorize the existing tracing methods according to the RGBT tracing framework. Then, we introduce the datasets/benchmarks used to evaluate RGBT tracking methods. Subsequently, we present the results of representative tracking methods on multiple testing benchmarks, providing a more intuitive presentation of current research advances in the field of RGBT tracking. Finally, research directions are discussed to further advance the development of RGBT tracking.