使用快速水平集方法进行对象跟踪的遮挡处理

J. Gambini, Damian Rozichner, M. Buemi, M. Mejail, J. Jacobo-Berlles
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引用次数: 1

摘要

在图像序列中,由于物体和人之间经常出现遮挡,跟踪目标是一个难题。本文提出了一种基于水平集技术的目标遮挡跟踪方法。考虑两种情况:1-物体被另一个不同颜色的物体阻挡。物体被另一个相同颜色的物体挡住了。在第一种情况下,基于活动轮廓的经典算法无法跟踪物体的轮廓,因为曲线从场景中消失了。在这个方案中,遮挡被检测到,解决方案是基于保持曲线在同一位置,直到感兴趣的物体再次出现在场景中。在第二种情况下,基于活动轮廓的经典算法无法区分相同颜色的两个图像对象,因此由于拓扑结构可能发生变化,曲线拟合两个对象的边缘并被分割。我们通过曲线质心的局部化来解决这个问题。实验结果表明,这些方法显著改善了遮挡下的跟踪效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Occlusion Handling for Object Tracking Using a Fast Level Set Method
Tracking objects in image sequences is a difficult problem because of the frequent occlusions encountered among the objects and people. In this paper, a method for tracking objects through occlusions based on a level set technique, is presented. Two ca.ses are considered: 1-the object is obstructed by another one of a different color. 2-the object is obstructed by another one of the same color.In the first case, the classical algorithms based on active contours fail to track the object's contour because the curve disappears from the scene. In this proposal, occlusion is detected and the solution is based on keeping the curve in the same place until the object of interest appears in the scene again.In the second case, the classic algorithms based on active contours do not distinguish between two image objects of the same color, so due to the possible changes in the topology, the curve fits the edge of both objects and it is divided. We solve this problem by means of localizing the centroid of the curve.The experimental results show that these methods significantly improve the tracking with occlusions.
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