期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2013
卷号：XL-5/W1
页码：81-86
DOI：10.5194/isprsarchives-XL-5-W1-81-2013
出版社：Copernicus Publications
摘要：The paper presents a robust version of a recent anisotropic orthogonal Procrustes algorithm that has been proposed to solve the socalled camera exterior orientation problem in computer vision and photogrammetry. In order to identify outliers, that are common in visual data, we propose an algorithm based on Least Median of Squares to detect a minimal outliers-free sample, and a Forward Search procedure, used to augment the inliers set one sample at a time. Experiments with synthetic data demonstrate that, when the percentage of outliers is greater than 30% or the data size is small, the proposed method is more accurate in detecting outliers than the customary detection based on median absolute deviation
关键词：Robust Methods; Anisotropic Orthogonal Procrustes Analysis; Camera Exterior Orientation
