Online Tracking via Stabilizer and Attractor
Xiang Ao, Feng Guo, Ying Lin, Jie Dong · Applied Mechanics and Materials · 2014
In this paper, we propose a novel, online, long-term tracking algorithm to track objects that possess fairly regular motion. Our tracker contains two terms: stabilizer and attractor. The stabilizer narrows the candidate location of an object at the next frame in a sequence by employing the Kalman filter, which enhances the speed of our tracker and brings stability. The attractor is an inner template of an object consisting of Harris corner pairs. By excluding distractors with a different inner template, our tracker is discriminative and accurate. Experiments on several benchmark sequences show our competitive performance.