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Journal ArticleDOI

A theory of self-calibration of a moving camera

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TLDR
The feasibility of camera calibration based on the epipolar transformation is demonstrated and two curves of degree six can be obtained in the dual plane such that one of the real intersections of the two yields the correct camera calibration.
Abstract
There is a close connection between the calibration of a single camera and the epipolar transformation obtained when the camera undergoes a displacement. The epipolar transformation imposes two algebraic constraints on the camera calibration. If two epipolar transformations, arising from different camera displacements, are available then the compatible camera calibrations are parameterized by an algebraic curve of genus four. The curve can be represented either by a space curve of degree seven contained in the intersection of two cubic surfaces, or by a curve of degree six in the dual of the image plane. The curve in the dual plane has one singular point of order three and three singular points of order two. If three epipolar transformations are available, then two curves of degree six can be obtained in the dual plane such that one of the real intersections of the two yields the correct camera calibration. The two curves have a common singular point of order three. Experimental results are given to demonstrate the feasibility of camera calibration based on the epipolar transformation. The real intersections of the two dual curves are found by locating the zeros of a function defined on the interval [0, 2π]. The intersection yielding the correct camera calibration is picked out by referring back to the three epipolar transformations.

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Citations
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Journal ArticleDOI

A flexible new technique for camera calibration

TL;DR: A flexible technique to easily calibrate a camera that only requires the camera to observe a planar pattern shown at a few (at least two) different orientations is proposed and advances 3D computer vision one more step from laboratory environments to real world use.
Proceedings ArticleDOI

Flexible camera calibration by viewing a plane from unknown orientations

TL;DR: Compared with classical techniques which use expensive equipment, such as two or three orthogonal planes, the proposed technique is easy to use and flexible, and advances 3D computer vision one step from laboratory environments to real-world use.
Journal ArticleDOI

A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry

TL;DR: A robust approach to image matching by exploiting the only available geometric constraint, namely, the epipolar constraint, is proposed and a new strategy for updating matches is developed, which only selects those matches having both high matching support and low matching ambiguity.
Journal ArticleDOI

Determining the Epipolar Geometry and its Uncertainty: A Review

TL;DR: A complete review of the current techniques for estimating the fundamental matrix and its uncertainty is provided, and a well-founded measure is proposed to compare these techniques.
References
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Book

Robot Vision

TL;DR: Robot Vision as discussed by the authors is a broad overview of the field of computer vision, using a consistent notation based on a detailed understanding of the image formation process, which can provide a useful and current reference for professionals working in the fields of machine vision, image processing, and pattern recognition.
Book

Mathematica: A System for Doing Mathematics by Computer

TL;DR: This book will be released simultaneously with Release 2.0 of Mathematica and will cover all the new features of Release 1.0 as mentioned in this paper, including 16 pages of full-color graphics.
Proceedings Article

Robot vision

TL;DR: A scheme is developed for classifying the types of motion perceived by a humanlike robot and equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented.
Book

Algebraic curves

TL;DR: A linear transformation with rational maps riemann sphere is presented in this article, where the presentation is kept as elementary as A linear transformations with rational map Riemann spheres the converse is where sense.