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Statistical estimation for exterior orientation from line-to-line correspondences

  • Chung-Nan Lee
  • Robert M. Haralick
Session IA2a — 3-D Image Analysis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)

Abstract

This paper presents a statistical estimation from which a new objective function for exterior orientation from line correspondences is derived. The objective function is based on the assumption that the underlying noise model for the line correspondences is the Fisher distribution. The assumption is appropriate for 3D orientation, is different from the underlying noise models for k pixels positions, and allows us to do a consistent estimation of the unknown parameters. The objective function gives two important facts: its formulation and concept is different for that of previous work, and it automatically estimates six unknown parameters simultaneously. As a result, it provides an optimal solution and better accuracy. We design an experimental protocol to evaluate the performance of the new algorithm. The results of each experiment shows that the new algorithm produces answers whose errors are 10%–20% less than the competing decoupled least squares algorithm.

Keywords

Translation Vector Fisher Distribution World Coordinate System Exterior Orientation Line Correspondence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Chung-Nan Lee
    • 1
  • Robert M. Haralick
    • 2
  1. 1.Institute of Computer and Information EngineeringNational Sun Yat-Sen University KaohsiungTaiwan, 80424, ROC
  2. 2.Intelligent Systems Laboratory, Department of Electrical Engineering • FT-10University of WashingtonSeattleUSA

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