Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (14): 191-198.

Research on TLD improved target tracking algorithm for video surveillance

CHANG Libo1，2, DU Huimin1, MAO Zhili1, ZHANG Shengbing2, GUO Chongyu1, JIANG Bianbian1

1. 1.School of Electronic Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
2.School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China
• Online:2018-07-15 Published:2018-08-06

面向视频监控的TLD改进目标跟踪算法研究

1. 1.西安邮电大学 电子工程学院，西安 710121
2.西北工业大学 计算机学院，西安 710072

Abstract: At present, intelligent video surveillance has made a high demand for real-time, accuracy and robustness of video target tracking algorithm, but the existing algorithms cannot fully meet the application requirements. In this paper, a foreground classification algorithm based on Visual Background extractor（ViBe） is proposed to improve the speed of TLD detection target. The tracker in TLD framework is realized by Kernel Correlation Filter（KCF）, which improves the accuracy and robustness of the algorithm. To verify the feasibility of the proposed algorithm, OTB-2013 benchmark for video surveillance using is tested and compared with the other four representative tracking algorithms. The experimental results show that the improved TLD algorithm is superior to the contrast algorithm in the robustness and accuracy, and the processing speed can reach 40 frame/s. Compared with the standard TLD algorithm, the tracking distance is improved by 1.52 times and the success rate is improved by 1.2 times. Compared with the KCF algorithm, the tracking speed is improved by 2.7 times and the success rate is 2.04 times.