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Multiple View Geometry in Computer Vision

Hartley, Richard, Zisserman, Andrew·2004·Cambridge University Press eBooks

DOI 10.1017/cbo9780511811685

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Abstract

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

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Authors: Hartley, R., & Zisserman, A.
Affiliations: Australian National University (AU)
University of Oxford (GB)
ORCID: Hartley, Richard
Zisserman, Andrew
Venue: Cambridge University Press eBooks
Publisher: Cambridge University Press
Published: 2004-03-25
DOI: 10.1017/cbo9780511811685
OpenAlex: W2033819227
Cited by: 21,070
References: 0
Citations by year: 2026: 534 · 2025: 702 · 2024: 706 · 2023: 719 · 2022: 657 · 2021: 991 · 2020: 989 · 2019: 1057 · 2018: 974 · 2017: 1026 · 2016: 1026 · 2015: 1120 · 2014: 1162 · 2013: 1172 · 2012: 1057
FWCI: 165.02
Type: book
Language: en
Open access: closed
Licence: www.cambridge.org/core/terms (unspecified, 2497 d)
Locations: Cambridge University Press eBooks (publishedVersion)
CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Optical measurement and interference techniques
Keywords: multi-view geometry, projective geometry, fundamental matrix, trifocal tensor, scene reconstruction, photogrammetry, structure from motion, camera pose estimation, image correspondence

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Multiple View Geometry in Computer Vision

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