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Received: 2007-01-10

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Journal of Zhejiang University SCIENCE A 2007 Vol.8 No.10 P.1614~1623


A practical iterative two-view metric reconstruction with uncalibrated cameras

Author(s):  ZHOU Yong-jun, KOU Xin-jian

Affiliation(s):  Schoo1 of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Corresponding email(s):   yjzhou@sjtu.edu.cn

Key Words:  Close-range photogrammetry, Computer vision, General relative orientation, Unit quaternion, Metric reconstruction

ZHOU Yong-jun, KOU Xin-jian. A practical iterative two-view metric reconstruction with uncalibrated cameras[J]. Journal of Zhejiang University Science A, 2007, 8(10): 1614~1623.

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author="ZHOU Yong-jun, KOU Xin-jian",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T A practical iterative two-view metric reconstruction with uncalibrated cameras
%A ZHOU Yong-jun
%A KOU Xin-jian
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A1614

T1 - A practical iterative two-view metric reconstruction with uncalibrated cameras
A1 - ZHOU Yong-jun
A1 - KOU Xin-jian
J0 - Journal of Zhejiang University Science A
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IS - 10
SP - 1614
EP - 1623
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2007.A1614

This paper presents a practical iterative algorithm for two-view metric reconstruction without any prior knowledge about the scene and motion in a nonsingular geometry configuration. The principal point is assumed to locate at the image center with zero skew and the same aspect ratio, and the interior parameters are fixed, so the self-calibration becomes focal-length calibration. Existing focal length calibration methods are direct solutions of a quadric composed of fundamental matrix, which are sensitive to noise. A quaternion-based linear iterative Least-Square Method is proposed in this paper, and one-dimensional searching for optimal focal length in a constrained region instead of solving optimization problems with inequality constraints is applied to simplify the computation complexity, then unique rotational matrix and translate vector are recovered. Experiments with simulation data and real images are given to verify the algorithm.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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