摘要
针对固定搜索窗口均值漂移算法在目标运动速度过快或目标尺度发生变化而导致跟踪失败的问题,提出一种与卡尔曼滤波相结合的自适应窗口跟踪算法。首先用卡尔曼滤波算法对运动目标进行预测及更正,设定感兴趣区域,并利用均值漂移算法确定搜索窗口大小和位置,同时结合Bhattacharyya系数进行目标定位,实现视频中目标跟踪。通过对比分析和实验结果,改进算法对目标尺度发生变形时具有较好的鲁棒性和准确性。
Mean shift algorithm with fixed searching window may fail in tracking due to the target moving too fast or the variation in target scale. Aiming at this problem,we propose a tracking algorithm with adaptive window which combines the Kalman filtering. First the Kalman filter algorithm is used to predict and correct the moving target,and to set the region of interest; then the mean shift algorithm is used to determine the size and position of search window,and at the same time the Bhattacharyya coefficient is used to locate the target and to realise the targets tracking in video. Through comparative analysis and experimental results,it is proved that the proposed algorithm has good robustness and accuracy on deformation of target scales.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第5期240-243,共4页
Computer Applications and Software
