多技术融合的Mean-Shift目标跟踪算法  

A M ean-Shift target tracking algorithm fused multi technology

作　　者：郭志波[1] 董健[1] 庞成[1] 

机构地区：[1]扬州大学信息工程学院,江苏扬州225009

出　　处：《山东大学学报（工学版）》2015年第2期10-16,共7页Journal of Shandong University（Engineering Science）

基　　金：教育部科学技术研究重点资助项目(311024);江苏省"六大人才高峰"资助项目(2013DZXX023)

摘　　要：在研究经典算法的基础上,提出了一种多技术融合的Mean-Shift目标跟踪算法,有效地解决了经典MeanShift跟踪算法存在的缺陷。通过Kalman算法预测估计目标的中心位置,通过分块颜色直方图提取目标区域的空间信息进行,同时采用背景加权和核加权相结合的方式抑制背景像素对目标的干扰。在多个视频数据上的试验结果表明,研究方法有效地克服了经典的Mean-Shift目标跟踪算法对遮挡、背景像素敏感的问题,在复杂环境的背景下对运动目标跟踪更加准确。Based on the study of classic algorithm, a Mean-Shift target tracking algorithm fused multi-technology was proposed, and the defects of the classic Mean-Shift tracking algorithm were solved. The center position of target was es- timated by the Kalman algorithm. The space information of the target area was extracted using the block color histo- gram. The combination approach of the background weighted and nuclear weighted was used to suppress the interference of background pixels on the target. The experiments resulted on several video data showed that the new method fused three kinds of technology effectively overcame the barrier and background pixel sensitive problem, and had more accu- rate tracking than classic Mean-Shift target tracking algorithm under complex environment.

关 键 词：MEAN-SHIFT算法 目标跟踪 Kalman预测器 分块颜色直方图 背景加权 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]