Departmental Papers (CIS)

Date of this Version

May 2003

Document Type

Journal Article

Comments

Copyright 2003 IEEE. Reprinted from IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 25, Issue 5, May 2003, pages 578-589.
Publisher URL: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isNumber=26906&puNumber=34

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Abstract

Estimation of camera pose from an image of n points or lines with known correspondence is a thoroughly studied problem in computer vision. Most solutions are iterative and depend on nonlinear optimization of some geometric constraint, either on the world coordinates or on the projections to the image plane. For real-time applications, we are interested in linear or closed-form solutions free of initialization. We present a general framework which allows for a novel set of linear solutions to the pose estimation problem for both n points and n lines. We then analyze the sensitivity of our solutions to image noise and show that the sensitivity analysis can be used as a conservative predictor of error for our algorithms. We present a number of simulations which compare our results to two other recent linear algorithms, as well as to iterative approaches. We conclude with tests on real imagery in an augmented reality setup.

Keywords

Pose estimation, exterior orientation, absolute orientation, camera localization

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Date Posted: 01 November 2004

This document has been peer reviewed.