关键词: 目标跟踪, 压缩感知, 特征融合, 实时跟踪

Abstract: As real-time compressive tracking algorithm cannot steadily track object when appearance of target or external environment change heavily, compressive tracking method based on adaptive feature fusion is proposed. Two random measurement matrices are adopted to obtain texture and color features from V and H channel respectively. Then relative reliability index is used to calculate weights which can be update online, and two features are combined to improve tracking performance based on their own advantages. Testing results on challenging videos show that the proposed method can track object stably when target appearance or external environment change heavily. The method can run in real-time that the average frame rate is 22 frames/s when the target scale is 70　pixel×100　pixel. The proposed method is more robust in comparison with the compressive tracking algorithm which extracting single feature.

Key words: object tracking, compressive sensing, feature fusion, real-time tracking