A Novel Robust Contour Tracking Algorithm

Jianjun Xu, Duyan Bi, Zifu Wei
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引用次数: 2

Abstract

Under the conditions of fasting moving, shape changing and partial occlusion of target, Now mostly tracking algorithms are difficult to get accurate contour of target, for these problems, a novel contour tracking algorithm based on particle filter and fast level set is proposed. Firstly, the particle filter algorithm is adopted to estimate moving target’s boundary contour. Then, according to the nearest neighbor decision method, a new the velocity function of fast level set is found, the strongpoint of the function is that the tracking algorithm is fit for target and background changing. Finally, the contour tracking is realized by evolving the zero level set curve using fast level set algorithm which is proposed in this paper. Experiments for representative image sequences show that this algorithm can track the rigid and non-rigid target contour under the complex environments. The result indicates that this algorithm is robust and accurate compared with other tracking algorithms.
一种新的鲁棒轮廓跟踪算法
针对目标在快速运动、形状变化和部分遮挡等条件下难以准确得到目标轮廓的问题,提出了一种基于粒子滤波和快速水平集的目标轮廓跟踪算法。首先,采用粒子滤波算法估计运动目标的边界轮廓;然后,根据最近邻决策方法,找到了一种新的快速水平集速度函数,该函数的优点是跟踪算法适合目标和背景的变化。最后,利用本文提出的快速水平集算法对零水平集曲线进行演化,实现轮廓跟踪。具有代表性的图像序列实验表明,该算法能够在复杂环境下对刚性和非刚性目标轮廓进行跟踪。结果表明,与其他跟踪算法相比,该算法具有较好的鲁棒性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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