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Simultaneous Tracking of Multiple Objects Using Fast Level Set-Like Algorithm

机译:使用快速水平集样算法同时跟踪多个对象

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A topological flexibility of implicit active contours is of great benefit, since it allows simultaneous detection of several objects without any a priori knowledge about their number and shapes. However, in tracking applications it is often required to keep desired objects mutually separated as well as allow each object to evolve itself, i.e., different objects cannot be merged together, but each object can split into several regions that can be merged again later in time. The former can be achieved by applying topology-preserving constraints exploiting either various repelling forces or the simple point concept from digital geometry, which brings, however, an indispensable increase in the execution time and also prevent the latter. In this paper, we propose more efficient and more flexible topology-preserving constraint based on a region indication function, that can be easily integrated into a fast level set-like algorithm [Maska, Matula, Danek, Kozubek, LNCS 6455, 2010] in order to obtain a fast and robust algorithm for simultaneous tracking of multiple objects. The potential of the modified algorithm is demonstrated on both synthetic and real image data.
机译:隐式活动轮廓的拓扑灵活性非常有用,因为它可以同时检测多个对象,而无需先验其数量和形状。但是,在跟踪应用程序中,通常需要使所需的对象相互分离,并允许每个对象自行发展,即,不同的对象无法合并在一起,但是每个对象可以拆分为多个区域,可以稍后再合并。前者可以通过利用各种排斥力或数字几何中的简单点概念来应用保留拓扑的约束来实现,但是这带来了执行时间的必不可少的增加,并且也阻止了后者。在本文中,我们提出了一种基于区域指示函数的更有效,更灵活的拓扑保留约束,可以轻松地将其集成到类似快速级别集的算法中[Maska,Matula,Danek,Kozubek,LNCS 6455、2010]为了获得用于同时跟踪多个对象的快速且鲁棒的算法。修改后的算法在合成图像数据和真实图像数据上都有潜力。

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