A review on video object tracking algorithms
Feifei Zhou, William Penaflor Rey · 2024
Video object tracking is an important research direction in the field of computer vision, with applications spanning a wide range of fields such as video surveillance, intelligent transportation, and human-computer interaction. With the rapid development of technology, a large number of new algorithms have emerged in the field, significantly improving accuracy, speed and robustness. This review article delves into the evolution of algorithms, tracing their progression from early tracking algorithms to correlation filter tracking and deep learning tracking algorithms. It introduces the definition of video object tracking algorithms and expounds upon their historical background. By comparing and analyzing these algorithms, their distinct performance, characteristics, advantages, disadvantages, applicable scenarios, and potential areas for improvement become more evident. The article further explores technological advancements, challenges encountered, evaluation methods for algorithms, and research progress, while offering perspectives on future trends.