偏移校正的核空间直方图目标跟踪  

Kernel Spatial Histogram Target Tracking Based on Template Drift Correction

作　　者：王勇[1] 陈分雄[1] 郭红想[1] 

机构地区：[1]中国地质大学机电学院,武汉430074

出　　处：《自动化学报》2012年第3期430-436,共7页Acta Automatica Sinica

基　　金：中央高校基本科研业务费专项资金(CUGL090240)资助~~

摘　　要：针对传统均值漂移算法中核函数直方图对目标特征描述较弱、跟踪窗不能动态调整容易导致目标跟偏或跟丢的缺点,提出了一种改进的均值漂移跟踪算法.为提高目标特征描述的可靠性,采用二阶空间直方图建立目标模型,以Bhattacharyya系数作为相似性度量;通过偏移校正更新目标区域参数建立新的目标模型;结合边缘与角点检测选取特征点建立仿射模型实现跟踪窗的调整;根据卡尔曼残差判断目标是否被遮挡,从而选择卡尔曼滤波或是线性预测来确定目标位置.实验结果表明,该算法可以准确地跟踪目标,对相似背景干扰、目标大小与方向的变化以及短时遮挡具有鲁棒性.Aiming at the limitations of the traditional mean shift, such as invariable kernel bandwidth, inadequate color distribution representation of target and the accumulative tracking errors, an improved tracking algorithm with the following strategies is proposed. The target model and the candidate are described by a modified second-order spatial histogram including color and spatial information, and the similarity between them is evaluated by Bhattacharyya coefficient. According to the target region parameter resulted from template drift correction which can eliminate the tracking errors, the target model can be estimated repeatedly. The tracking region parameters are updated through an affine transform combining corner detection and edge detection. Besides, the target motion is predicted by either Kalman filter or linear filter according to the Kalman residual error. Experimental results show that the proposed algorithm is robust against similarity distraction, scale and orientation variations and short-term occlusion.

关 键 词：目标跟踪 均值漂移算法 空间直方图 偏移校正 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]