A Robust Algorithm for Point Set Registration Using Mixture of Gaussians.

Bing Jian, Baba C Vemuri
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引用次数: 380

Abstract

This paper proposes a novel and robust approach to the point set registration problem in the presence of large amounts of noise and outliers. Each of the point sets is represented by a mixture of Gaussians and the point set registration is treated as a problem of aligning the two mixtures. We derive a closed-form expression for the L(2) distance between two Gaussian mixtures, which in turn leads to a computationally efficient registration algorithm. This new algorithm has an intuitive interpretation, is simple to implement and exhibits inherent statistical robustness. Experimental results indicate that our algorithm achieves very good performance in terms of both robustness and accuracy.

一种基于混合高斯的点集配准鲁棒算法。
针对存在大量噪声和异常值的点集配准问题,提出了一种新颖的鲁棒方法。每个点集都由高斯分布的混合表示,点集配准被视为两个混合的对齐问题。我们推导了两个高斯混合物之间的L(2)距离的封闭表达式,这反过来又导致了计算效率高的配准算法。该算法具有直观的解释、简单的实现和固有的统计鲁棒性。实验结果表明,该算法在鲁棒性和准确性方面都取得了很好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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