关键词: 视觉跟踪, 线性表示, 在线更新, 离群值, 自适应权重矩阵

Abstract: To solve the problems of poor robustness and low effectiveness of visual tracking in complex scenes, this paper proposes a target tracking algorithm based on adaptive observation weight in Bayesian framework. Firstly, a weighted observation model is established via linear visual tracking representation. Then an iterative optimization algorithm is put forward to adaptively update the weight matrix to eliminate negative influences of observation outliers. Finally, effective likelihood evaluation function is adopted to capture the target accurately. The experimental results show that the proposed algorithm outperforms other state-of-the-art tracking algorithms in tracking accuracy and robustness.

Key words: visual tracking, linear representation, on-line updating, outliers, adaptive weight matrix