Overview
- Presents the first linear method to calibrate all central projection systems and fisheye cameras
- Introduces a generic approach to obtain the scale space of any central projection system, by combining the Riemannian geometry with the sphere camera model
- Explores the role of hybrid two-view relations to construct robust matching approaches
- Examines the problem of extracting conics from catadioptric images that represent the projections of straight lines
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This work focuses on central catadioptric systems, from the early step of calibration to high-level tasks such as 3D information retrieval. The book opens with a thorough introduction to the sphere camera model, along with an analysis of the relation between this model and actual central catadioptric systems. Then, a new approach to calibrate any single-viewpoint catadioptric camera is described. This is followed by an analysis of existing methods for calibrating central omnivision systems, and a detailed examination of hybrid two-view relations that combine images acquired with uncalibrated central catadioptric systems and conventional cameras. In the remaining chapters, the book discusses a new method to compute the scale space of any omnidirectional image acquired with a central catadioptric system, and a technique for computing the orientation of a hand-held omnidirectional catadioptric camera.
Authors and Affiliations
Bibliographic Information
Book Title: Omnidirectional Vision Systems
Book Subtitle: Calibration, Feature Extraction and 3D Information
Authors: Luis Puig, J.J. Guerrero
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-1-4471-4947-7
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Luis Puig 2013
Softcover ISBN: 978-1-4471-4946-0Published: 02 February 2013
eBook ISBN: 978-1-4471-4947-7Published: 01 February 2013
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XI, 122
Number of Illustrations: 33 b/w illustrations, 35 illustrations in colour
Topics: Image Processing and Computer Vision, Artificial Intelligence, Robotics and Automation