基于动态和静态度量的视觉目标跟踪研究

Lichao Zhang, Duyan Bi, Yufei Zha, Dong Nan, Li Zhou
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引用次数: 0

摘要

经典核跟踪算法在目标模型中使用了颜色特征,但静态特征难以适应背景中与目标颜色分布相似的突然运动和旋转的变化目标。考虑到经典光流提取的局部动态特征能够描述目标的动态特性,提出了一种基于动态度量的跟踪方法。为了获得准确的表示,采用方差矩阵估计自适应物体尺度和旋转的误差椭圆。实验表明,在复杂背景下,当目标发生突然运动和旋转时,与其他相关算法相比,该算法可以获得更好的跟踪效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on visual object tracking by dynamic and static metric
Color feature is used in object model of classical kernel tracking algorithm, but the static feature is hard to adapt to the changing object with abrupt movement and rotation in the background whose color distribution is similar to object's. Considering that local dynamic feature extracted by classical optical flow can describe the object's dynamic characteristics, a new tracking method is proposed based on dynamic metric. In order to obtain accurate denotation, the variance matrix is used to estimate the error ellipse which is adaptive to the object's scale and rotation. The experiments show that the proposed algorithm can achieve better tracking results compared with other related algorithms when the target moves abruptly and rotates under the condition of complicated background.
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