基于双感兴趣区域判定和速度信息融合的CamShift目标跟踪算法

Object Tracking Algorithm Based on CamShift with Dual ROI and Velocity Information Fusion

  • 摘要: 针对连续自适应均值偏移(CamShift)算法易受相似色的影响,从而导致跟踪发散和跟踪目标丢失后无法重新获取的现象,提出了一种基于双感兴趣区域(ROI)判定并融入速度信息的CamShift运动目标跟踪方法.算法的基本思想是将单个ROI划分为两个子ROI,其中一个为主跟踪区域,另一个为辅助跟踪区域,采用两个独立的跟踪器分别对其进行跟踪,通过两个跟踪器在跟踪中的协调解决了相似色干扰问题,增强了跟踪算法的鲁棒性,同时,将目标的速度信息引入跟踪算法.实验结果表明,即使受到相似色干扰和遮挡,这种改进后的CamShift算法仍然能够保持对目标的有效跟踪.

     

    Abstract: In order to deal with the tracking divergence and the recapturing failure after occlusion of the continuously adaptive mean Shift algorithm(CamShift) to track objects passing the background with similar colours to them,an improved CamShift algorithm with dual region of interest(ROI) and velocity information fusion is proposed to track moving objects.The main idea of the algorithm is to divide the single ROI which is used to specify the region to be tracked in CamShift into two sub ROIs,of which one is the primary tracking region and the other one is the auxiliary tacking region.For each of these two sub ROIs,a CamShift tracker is designed respectively.Through the coordination of these two CamShift trackers in the process of tracking,the tracking robustness of the algorithm is enhanced and the interference problem due to similar colour in the CamShift is solved.Meanwhile,the velocity information of the tracked object is introduced into the CamShift tracker to enable the algorithm to relocate the tracking target after occlusion.Experimental results demonstrate that the proposed CamShift with dual ROI can effectively track the object even when it is affected or occluded by things with similar colours.

     

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