Volume XL-5/W1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W1, 81-86, 2013
https://doi.org/10.5194/isprsarchives-XL-5-W1-81-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W1, 81-86, 2013
https://doi.org/10.5194/isprsarchives-XL-5-W1-81-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  13 Feb 2013

13 Feb 2013

RELIABLE EXTERIOR ORIENTATION BY A ROBUST ANISOTROPIC ORTHOGONAL PROCRUSTES ALGORITHM

A. Fusiello1, E. Maset2, and F. Crosilla2 A. Fusiello et al.
  • 1Dipartimento di Ingegneria Elettrica, Gestionale e Meccanica, University of Udine, Via Delle Scienze, 208-33100 Udine, Italy
  • 2Dipartimento di Ingegneria Civile e Architettura, University of Udine, Via Delle Scienze, 208-33100 Udine, Italy

Keywords: Robust Methods, Anisotropic Orthogonal Procrustes Analysis, Camera Exterior Orientation

Abstract. 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.