一种基于改进贪心蛇的轮廓跟踪算法

Sajjad Torkan, A. Behrad
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引用次数: 12

摘要

本文提出了一种新的基于活动轮廓的跟踪方法。原始贪心蛇形作为一种参数化主动轮廓,在高速度、大位移的连续两帧目标跟踪中表现不佳。这是由于目标边界部分凹进去,轮廓距离目标边界较远会收缩,缺乏目标运动信息。为了解决这些问题,我们提出了一种具有自适应曲率能量和附加场能量项作为外部能量的贪心蛇。第三个问题是利用卡尔曼滤波对初始轮廓在当前帧中的位置进行估计。在真实视频序列上的实验表明,该方法可以很好地跟踪连续帧中的目标轮廓,并且对摄像机运动(包括变焦和振动)具有鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new contour based tracking algorithm using improved greedy snake
In this paper, we introduce a new contour based tracking method using active contour. Original greedy snake as a parametric active contour has weak performance in tracking target with high velocity and large displacement between two successive frames. This is due to concave parts of target boundary, shrinkage of contour if it is far from target boundary and the lack of target motion information. To cope with these problems we proposed a greedy snake with adaptive curvature energy and additional field energy term as an external energy. Third problem is handled by Kalman filter which is used in the proposed tracking algorithm for estimation of location of initial contour in the current frame. Several experiments on real video sequences show that our method can track target contour in successive frames perfectly and is robust against camera movements including zooming and vibrations.
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