Improved Tracking-Learning-Detection Human Tracking Algorithm

Abstract

For the problem that appearance of human will be changed in motion, it is a challenge to those capabilities of tracker, related to adaptation of human appearance. In the paper, an improved Tracking-Learning-Detection algorithm, including short-term-tracking, real-time-detection and online-learning, is proposed. Furthermore, scale-invariant feature is applied to the short-term-tracking to determine the location of target in consecutive frames. The video stream of the PETS2006 database is utilized to evaluate the proposed algorithm. Experiments results demonstrate the effectiveness, especially on the short-term-tracking performance.