关键词: 压缩跟踪, 漂移, 局部敏感直方图, 光照不变特征, 多示例学习

Abstract: As traditional tracking algorithm based on compressive sensing is failed to track target stably when illumination and target position get seriously changed, a reformative target tracking algorithm based on locality sensitive histograms is proposed. By calculating the locality sensitive histograms, extracting illumination invariant features, the jointed features are used in compressive tracking. Results of tests on variant video sequences show that the proposed algorithm has advantages over compressive tracking and multiple instance learning tracking in target positions and lightings changing heavily. Obtained results satisfy the requirements of real-time tracking.

Key words: compressive tracking, drift, locality sensitive histograms, illumination invariant features, multiple instance learning