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Level-Set Curve Particles

机译:水平设置曲线粒子

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摘要

In many applications it is necessary to track a moving and deforming boundary on the plane from infrequent, sparse measurements. For instance, each of a set of mobile observers may be able to tell the position of a point on the boundary. Often boundary components split, merge, appear, and disappear over time. Data are typically sparse and noisy and the underlying dynamics is uncertain. To address these issues, we use a particle filter to represent a distribution in the large space of all plane curves and propose a full-fledged combination of level sets and particle filters. Our main contribution is in controlling the potentially high expense of multiplying the cost of a level set representation of boundaries by the number of particles needed. Experiments on tracking the boundary of a colon in tomographic imagery from sparse edge measurements show the promise of the approach.
机译:在许多应用中,有必要通过罕见的稀疏测量来跟踪平面上的移动和变形边界。例如,一组移动观察者中的每一个都能够分辨出点在边界上的位置。边界成分通常会随时间分裂,合并,出现和消失。数据通常是稀疏且嘈杂的,其潜在动态是不确定的。为了解决这些问题,我们使用粒子滤波器表示所有平面曲线在较大空间中的分布,并提出了一套完整的水平集和粒子滤波器组合。我们的主要贡献在于控制将边界的水平集表示成本乘以所需粒子数量而可能产生的高额费用。通过稀疏边缘测量跟踪断层图像中结肠边界的实验表明了该方法的前景。

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