流形背景感知的相关滤波目标跟踪

Manifold Background-Aware Correlation Filter Target Tracking

针对相关滤波跟踪算法在相似背景、遮挡、快速运动、运动模糊等复杂场景下目标易丢失的问题,提出一种新的基于流形背景感知的相关滤波目标跟踪方法。首先,选取目标区域,提取目标的外观特征,建立目标模型;然后,以目标所在位置为原点,采用双指数分布构建流形搜索区域,并根据目标的运动速度和运动方向动态调整流形搜索区域的搜索范围和搜索角度,提取流形搜索区域内的背景信息,将背景信息与目标特征模型进行滤波器训练,得到滤波器模板;最后,以滤波器模板来确定目标位置,进行目标跟踪。提出的流形背景感知算法,根据目标运动的速度和方向,采用动态搜索机制进行搜索,涵盖了目标随机运动的大概率空间范围,在复杂场景下能够有效搜索目标,并控制了计算量,提升了目标跟踪算法的精度和速度。该方法在标准数据集OTB100上进行了大量的实验,实验结果表明,相较于其他主流算法,该算法对相似背景、遮挡、快速运动、运动模糊等复杂条件下的目标跟踪具有很好的准确率、实时性和鲁棒性。

In order to solve the problem that target is easy to lose in complex scenes such as similar background,occlusion,fast motion and motion blur,a new manifold background-aware correlation filter tracking algorithm is proposed.Firstly,the object tracking region is selected to extract the appearance features of target to establish object model.Then,taking target location as the origin,the manifold search area is constructed by using double expo-nential distribution.According to the target motion speed and direction,the manifold search range and search angle are dynamically adjusted.The background in the manifold search area is extracted,and the filter template is obtained by training the background information and the target feature model.Finally,the filter template is used to determine the target position and track the target.According to the speed and direction of the target motion,the manifold background-aware algorithm proposed adopts dynamic search mechanism to search,which covers the prob-ability space range of the target random motion.It can effectively search targets in complex scenarios,control calculation quantity,and improve the accuracy and speed of the target tracking algorithm.A great quantity of experiments are carried out on the standard dataset OTB100.Experimental results indicate that the proposed algorithm has good performance in accuracy,real time and robustness for target tracking under complex conditions such as similar background,occlusion,fast motion and motion blur in comparison with other mainstream algorithms.