Focal length calibration from two views: method and analysis of singular cases

Authors:
P. Sturm;Z. L. Cheng;P. C. Y. Chen;A. N. Poo
Affiliations:
INRIA Rhône-Alpes, Montbonnot, St. Martin, France;Troy, NY and Mechanical Engineering Department, National University of Singapore, Singapore, Singapore;Bachelor of Technology Programme, Faculty of Engineering, National University of Singapore, Singapore, Singapore;Mechanical Engineering Department, National University of Singapore, Singapore, Singapore
Venue:
Computer Vision and Image Understanding
Year:
2005

Citing 14
Cited 1

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

Artificial Intelligence - Special volume on computer vision
Kruppa's Equations Derived from the Fundamental Matrix

IEEE Transactions on Pattern Analysis and Machine Intelligence
Triangulation

Computer Vision and Image Understanding
A Case Against Kruppa's Equations for Camera Self-Calibration

IEEE Transactions on Pattern Analysis and Machine Intelligence
Critical Motions for Auto-Calibration When Some Intrinsic Parameters Can Vary

Journal of Mathematical Imaging and Vision
Multiple view geometry in computer visiond

Multiple view geometry in computer visiond
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications

The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
Estimation of Relative Camera Positions for Uncalibrated Cameras

ECCV '92 Proceedings of the Second European Conference on Computer Vision
Camera Self-Calibration: Theory and Experiments

ECCV '92 Proceedings of the Second European Conference on Computer Vision
Euclidean Reconstruction from Image Sequences with Varying and Unknown Focal Length and Principal Point

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Critical Motion Sequences for Monocular Self-Calibration and Uncalibrated Euclidean Reconstruction

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
In defence of the 8-point algorithm

ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
From Projective to Euclidean Space Under any Practical Situation, a Criticism of Self-Calibration

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Self-Calibration and Metric Reconstruction in spite of Varying and Unknown Internal Camera Parameters

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision

Conic Geometry and Autocalibration from Two Images

Journal of Mathematical Imaging and Vision

Quantified Score

Hi-index	0.00

Visualization

Abstract

We consider the problem of estimating the focal length of a camera from two views while the focal length is not varied during the motion of the camera. An approach based on Kruppa's equations is proposed. Specifically, we derive two linear and one quadratic equations to solve the problem. Although the three equations are interdependent in general, each one may be singular for different configurations. We study in detail the generic singularities of the problem and the actual singularities of the individual calibration equations. Results of our experiments using synthetic and real data underline the effect that singular configurations may have on self-calibration. However, these results are stable once the singularities are avoided.