A new variational approach based on level-set function for convex hull problem with outliers

IF 1.2 4区 数学 Q2 MATHEMATICS, APPLIED
Lingfeng Li, Shousheng Luo, X. Tai, Jiang Yang, kaifeng China Algorithms
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引用次数: 6

Abstract

Seeking the convex hull of an object (or point set) is a very fundamental problem arising from various tasks. In this work, we propose a variational approach based on the level-set representation for convex hulls of 2-dimensional objects. This method can adapt to exact and inexact convex hull problems. In addition, this method can compute multiple convex hulls simultaneously. In this model, the convex hull is characterized by the zero sublevel-set of a level-set function. For the exact case, we require the zero sublevel-set to be convex and contain the whole given object, where the convexity is characterized by the non-negativity of Laplacian of the level-set function. Then, the convex hull can be obtained by minimizing the area of the zero sublevel-set. For the inexact case, instead of requiring all the given points are included, we penalize the distance from all given points to the zero sublevel-set. Especially, the inexact model can handle the convex hull problem of the given set with outliers very well, while most of the existing methods fail. An efficient numerical scheme using the alternating direction method of multipliers is developed. Numerical examples are given to demonstrate the advantages of the proposed methods.
一种基于水平集函数的凸壳问题变分方法
寻找物体(或点集)的凸包是各种任务中出现的一个非常基本的问题。在这项工作中,我们提出了一种基于二维物体凸壳的水平集表示的变分方法。该方法适用于精确和不精确凸包问题。此外,该方法可以同时计算多个凸包。在该模型中,凸包的特征是一个水平集函数的零子水平集。对于确切的情况,我们要求零子水平集是凸的,并且包含整个给定对象,其中凸性的特征是水平集函数的拉普拉斯函数的非负性。然后,通过最小化零子水平集的面积得到凸包。对于不精确的情况,我们不要求包含所有给定点,而是惩罚从所有给定点到零子水平集的距离。特别是,非精确模型可以很好地处理带有异常值的给定集合的凸包问题,而现有的大多数方法都失败了。利用乘法器的交替方向法,提出了一种有效的数值格式。数值算例说明了所提方法的优越性。
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来源期刊
Inverse Problems and Imaging
Inverse Problems and Imaging 数学-物理:数学物理
CiteScore
2.50
自引率
0.00%
发文量
55
审稿时长
>12 weeks
期刊介绍: Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.
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