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IEICE Transactions on Information and Systems 2007 E90-D(5):851-858; doi:10.1093/ietisy/e90-d.5.851
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Copyright © 2007 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Papers -- Image Recognition, Computer Vision

Uncalibrated Factorization Using a Variable Symmetric Affine Camera

Kenichi KANATANI1, Yasuyuki SUGAYA2 and Hanno ACKERMANN1

1 The authors are with the Department of Computer Science, Okayama University, Okayama-shi, 700–8530 Japan. E-mail: kanatani{at}suri.it.okayama-u.ac.jp, 2 The author is with the Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi-shi, 441–8580 Japan.


  Abstract

In order to reconstruct 3-D Euclidean shape by the Tomasi-Kanade factorization, one needs to specify an affine camera model such as orthographic, weak perspective, and paraperspective. We present a new method that does not require any such specific models. We show that a minimal requirement for an affine camera to mimic perspective projection leads to a unique camera model, called symmetric affine camera, which has two free functions. We determine their values from input images by linear computation and demonstrate by experiments that an appropriate camera model is automatically selected.

Key Words: factorization, structure from motion, affine camera, self-calibration, video image analysis

Manuscript received February 16, 2006. Manuscript revised October 12, 2006.


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