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Proceedings ArticleDOI

Automatic Camera Calibration with Structure and Motion Recovery from Two Views of a Polyhedral Structure

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TLDR
In this article, the authors propose an iterative linear algorithm that exploits the geometrical and algebraic constraints induced by rigidity and planarity in the scene to solve coplanar features segmentation, planar projective transferring, epipole computation, and all the plane intersections.
Abstract
This work addresses the problems of (i) self-calibration of a moving camera observing a 3D scene composed by planar structures and (ii) scene segmentation and reconstruction. Although there exist some works intending to deal with these problems, most of them are based on the estimation of the epipolar geometry, non-linear optimization, or linear systems that do not incorporate geometrical consistency and may produce undesirable side-effects. In this paper, we propose a novel iterative linear algorithm that exploits the geometrical and algebraic constraints induced by rigidity and planarity in the scene. Instead of solving a complex multi-linear problem, we solve iteratively several linear problems: coplanar features segmentation, planar projective transferring, epipole computation, and all the plane intersections. Linear methods allow our approach to be suitable for real-time localization and 3D reconstruction, e.g. for autonomous mobile robots applications. Furthermore, we avoid the explicit epipolar geometry computation and all the stability problems commonly associated with it.

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Journal ArticleDOI

Multistep Explicit Stereo Camera Calibration Approach to Improve Euclidean Accuracy of Large-Scale 3D Reconstruction

TL;DR: In this article, a set of multiple calibration parameters created by videotaping a moving calibration pattern along a specific path can increase overall calibration accuracy and ultimately enhance the Euclidean accuracy of the generated point cloud.
References
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Book

Multiple view geometry in computer vision

TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.

Multiple View Geometry in Computer Vision.

TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
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

Simultaneous linear estimation of multiple view geometry and lens distortion

TL;DR: This paper shows how linear estimation of the fundamental matrix from two-view point correspondences may be augmented to include one term of radial lens distortion, by expressing fundamental matrix estimation as a quadratic eigenvalue problem (QEP), for which efficient algorithms are well known.
Journal ArticleDOI

Motion and structure from motion in a piecewise planar environment

TL;DR: It is shown that when the environment is piecewise linear, it provides a powerful constraint on the kind of matches that exist between two images of the scene when the camera motion is unknown, and that this constraint can be recovered from an estimate of the matrix of this collineation.
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