Target tracking algorithm for pedestrians movement based on kernel-correlation filtering. Issue 10 (3rd October 2022) - Du, Feng; Wang, Wan-Liang; Zhang, Zhi
ABSTRACT: Objective: To reduce the effects of light changes, scale changes, local occlusion and other factors during target tracking, a kernel-correlation filtering (KCF) target tracking algorithm is introduced, which introduces the target block model. Results: Comparative experiments of multiple mainstream algorithms on multiple data sets. Experimental results show that the algorithm has the highest accuracy and success rate, which are 11.89% and 15.24% higher than the KCF algorithm, respectively, indicating that the algorithm proposed in this paper possesses a more sensitive response to changes in illumination. Among them, factors such as scale change and local occlusion are more robust.