关键词: 压缩跟踪, 梯度方向直方图, 多矩形平均, 多特征

Abstract: Compressive sensing theory is applied into object tracking area for a compressive tracking algorithm. It can better realize real-time tracking, but it?can easily cause?drift by only using rectangle samples of maximum classification?score value in complicated environment or occlusion. Moreover, the algorithm does not consider the factor of target scale. It presents a multi-feature compressive tracking algorithm based on gradients oriented histogram of local center area and multi-scale rectangle for these issues. It also proposes final object position determination by the average of multiple rectangle samples. Experimental?results show that the algorithm can effectively suppress the tracking drift and improve the accuracy and robustness of a tracking algorithm in such scenarios as violent object moving, occlusion and similar object interference.

Key words: compressive tracking, histogram of oriented gradients, average of multi-rectangle, multiple features