Machine Vision and Applications

, Volume 16, Issue 5, pp 321–329

Preemptive RANSAC for live structure and motion estimation

Original Paper

DOI: 10.1007/s00138-005-0006-y

Cite this article as:
Nistér, D. Machine Vision and Applications (2005) 16: 321. doi:10.1007/s00138-005-0006-y

Abstract

A system capable of performing robust live ego-motion estimation for perspective cameras is presented. The system is powered by random sample consensus with preemptive scoring of the motion hypotheses. A general statement of the problem of efficient preemptive scoring is given. Then a theoretical investigation of preemptive scoring under a simple inlier–outlier model is performed. A practical preemption scheme is proposed and it is shown that the preemption is powerful enough to enable robust live structure and motion estimation.

Keywords

Structure from motion Real-time Robust estimation 3D-Reconstruction Ego-motion 

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Sarnoff CorporationPrincetonUSA
  2. 2.Center for Visualization and Virtual Environments, Computer Science DepartmentUniversity of KentuckyLexingtonUSA

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