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Computer vision tasks include methods for acquiring, processing, ... ISBN 978-0-905705-71-2. Richard Szeliski (2010). Computer Vision: Algorithms and Applications ...
Foundations and Trends in Computer Graphics and Vision is a journal published by Now Publishers. It publishes survey and tutorial articles on all aspects of computer graphics and vision. [1] The editor-in-chiefs are Brian Curless (University of Washington), Luc Van Gool and Richard Szeliski (Microsoft Research). [citation needed]
Richard Szeliski, Image Alignment and Stitching: A Tutorial. Foundations and Trends in Computer Graphics and Computer Vision, 2:1-104, 2006. B. Fischer, J. Modersitzki: Ill-posed medicine – an introduction to image registration. Inverse Problems, 24:1–19, 2008; Barbara Zitová, Jan Flusser: Image registration methods: a survey. Image Vision ...
Computing Rectifying Homographies for Stereo Vision by Charles Loop and Zhengyou Zhang (April 8, 1999) Microsoft Research; Computer Vision: Algorithms and Applications, Section 11.1.1 "Rectification" by Richard Szeliski (September 3, 2010) Springerdheerajnkumar
Computer Vision, computational approaches to biological vision, applications of computer vision. Since the field of Computer Vision touches many fields (Computer Science, Engineering, Robotics, Biology, and others), we decided that this topic does not fit neatly within any other WikiProject. As such, we have created a separate project.
Special issue on Computational Photography, IEEE Computer, August 2006. Camera Culture and Computational Journalism: Capturing and Sharing Visual Experiences Archived 2015-09-06 at the Wayback Machine, IEEE CG&A Special Issue, Feb 2011. Rick Szeliski (2010), Computer Vision: Algorithms and Applications, Springer.
Correspondence is a fundamental problem in computer vision — influential computer vision researcher Takeo Kanade famously once said that the three fundamental problems of computer vision are: “Correspondence, correspondence, and correspondence!” [2] Indeed, correspondence is arguably the key building block in many related applications ...
In computer vision, the fundamental matrix is a 3×3 matrix which relates corresponding points in stereo images.In epipolar geometry, with homogeneous image coordinates, x and x′, of corresponding points in a stereo image pair, Fx describes a line (an epipolar line) on which the corresponding point x′ on the other image must lie.