SOAMST目标跟踪算法的改进应用研究  

Application of Improved SOAMST Target Tracking Algorithm

作　　者：肖钟捷[1,2] 杨升[1] 吴忠 

机构地区：[1]福建武夷学院数学与计算机学院,福建武夷山354300 [2]北京航空航天大学宇航学院,北京100191 [3]南平市公安局刑警支队,福建南平353000

出　　处：《长春大学学报》2014年第10期1311-1316,共6页Journal of Changchun University

基　　金：国家自然科学基金(61272351);福建省教育厅A类项目(JA14312)

摘　　要：基于视觉图像的飞行器目标跟踪中,一般要面临目标严重遮挡和目标大尺度形变等问题。为了实现这种情况下的准确目标定位和目标跟踪,提出采用融合卡尔曼滤波器的改进SOAMST算法:一方面利用卡尔曼滤波的递推与估计能力来解决目标运动过程中目标被遮挡的问题;另一方面使用基于大津阈值的改进SOAMST算法来处理运动目标的大尺度形变以实现目标的准确定位。实验结果表明,该算法能够处理运动目标的严重遮挡,实现对运动目标进行准确的定位和跟踪。In aircraft tracking based on visual images, serious target occlusion and large-scale deformation usually occur. In order to get precise position and target tracking in this case, an improved SOAMST algorithm adopted Kalman filter is put forward： on one hand, to solve the block problem of moving targets by recurrence and estimation ability of Kalman filter; on the other hand, to deal with large-scale deformation of moving targets by the improved SOAMST algorithm based on ostu threshold to achieve the goal of precise positioning. Experimental results show that the proposed method can handle severe occlusion of moving targets, realizing the accurate po- sitioning and tracking.

关 键 词：目标跟踪 卡尔曼滤波 抗遮挡 伸缩预测 算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]