Thermal Infrared Target Tracking: A Comprehensive Review

Thermal infrared (TIR) target tracking task is not affected by illumination changes and can be tracked at night, on rainy days, foggy days, and other extreme weather; so it is widely used in auxiliary driving, unmanned aerial vehicle reconnaissance, video surveillance, and other scenes. However, the TIR target tracking task also presents some challenges, such as intensity change, occlusion, deformation, similarity interference, and so on. These challenges significantly affect the performance of the TIR target tracking methods. To resolve these challenges in the TIR target tracking scenarios, numerous tracking methods have appeared in recent years. The purpose of this article is to give a comprehensive review and summary of the research status of the TIR target tracking methods. We first classify the TIR target tracking methods according to their frameworks and briefly summarize the advantages and disadvantages of different tracking methods, which can better understand the current research progress of the TIR target tracking methods. Next, the public datasets/benchmarks for performance testing of the TIR target tracking methods are introduced. Subsequently, we demonstrate the tracking results of several representative tracking methods on some datasets/benchmarks to more intuitively show the progress of the TIR target tracking methods made in the current research. Finally, we discussed the future research direction in an attempt to promote the better development of the TIR target-tracking tasks.