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Geometry of Multiple Affine Views

Long Quan 1 Yuichi Ohta 2 Roger Mohr 1
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : We introduce a unified framework for developing matching constraints of multiple affine views and rederive 2-view (affine epipolar geometry) and 3-view (affine image transfer) constraints within this framwork. With the insight into the particular structure of these multiple-view constraints, we first describe a new linear method for Euclidean motion and structure from 3 calibrated affine images. Compared with the existing linear method of Huang and Lee [6], the new method uses different and more appropriate constraints. It has no failure mode of the Euclidean factorisation method of Tomasi and Kanade [20]. We then describe how to integrate points and lines and establish some minimal point/line configurations for structure recovery. The method is demonstrated on real image sequences.
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https://hal.inria.fr/inria-00548329
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Submitted on : Monday, December 20, 2010 - 8:43:25 AM
Last modification on : Friday, June 26, 2020 - 4:04:03 PM

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Long Quan, Yuichi Ohta, Roger Mohr. Geometry of Multiple Affine Views. Workshop on 3D Structure from Multiple Images of Large-scale Environments (SMILE), Jan 1998, Freiburg, Germany. pp.32--46, ⟨10.1007/3-540-49437-5_3⟩. ⟨inria-00548329⟩

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