ROBUST OBJECT TRACKING USING JOINT COLOR-TEXTURE HISTOGRAM
ROBUST OBJECT TRACKING USING JOINT COLOR-TEXTURE HISTOGRAM
复制标题
使用联合颜色纹理直方图进行稳健的对象跟踪
DOI：
10.1142/s0218001409007624
复制
发表时间：
2009-11-01
影响因子：
1.5
通讯作者：
Wu, Chengke
中科院分区：
文献类型：
--
作者：
Ning, Jifeng;Zhang, Lei;Wu, Chengke
本文提出了一种新的目标跟踪算法，利用联合颜色-纹理直方图来表示目标，并将其应用到均值偏移框架中。除了传统的颜色直方图特征外，还采用局部二值模式（LBP）技术提取了目标的纹理特征来表示目标。利用主要均匀的LBP模式形成一个掩模，用于关节颜色纹理特征的选择。与传统的基于颜色直方图的整个目标区域跟踪算法相比，该算法有效地提取了目标区域的边缘和角点特征，表征效果更好，对目标的鲁棒性更强。实验结果表明，与标准均值漂移跟踪相比，该方法的均值漂移迭代次数少，大大提高了跟踪精度和效率。在目标和背景外观相似的复杂场景下，传统的基于颜色的方案可能无法对目标进行跟踪。
A novel object tracking algorithm is presented in this paper by using the joint color-texture histogram to represent a target and then applying it to the mean shift framework. Apart from the conventional color histogram features, the texture features of the object are also extracted by using the local binary pattern (LBP) technique to represent the object. The major uniform LBP patterns are exploited to form a mask for joint color-texture feature selection. Compared with the traditional color histogram based algorithms that use the whole target region for tracking, the proposed algorithm extracts effectively the edge and corner features in the target region, which characterize better and represent more robustly the target. The experimental results validate that the proposed method improves greatly the tracking accuracy and efficiency with fewer mean shift iterations than standard mean shift tracking. It can robustly track the target under complex scenes, such as similar target and background appearance, on which the traditional color based schemes may fail to track.