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Mixing catadioptric and perspective cameras
 in: Workshop on Omnidirectional Vision
, 2002
"... We analyze relations that exist between multiple views of a static scene, where the views can be taken by any mixture of paracatadioptric, perspective or affine cameras. Concretely, we introduce the notion of fundamental matrix, trifocal and quadrifocal tensors for the different possible combinatio ..."
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Cited by 37 (14 self)
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We analyze relations that exist between multiple views of a static scene, where the views can be taken by any mixture of paracatadioptric, perspective or affine cameras. Concretely, we introduce the notion of fundamental matrix, trifocal and quadrifocal tensors for the different possible combinations of these camera types. We also introduce the notion of plane homography for mixed image pairs. Generally speaking, these novel multiview relations may form the basis for the typical geometric computations like motion estimation, 3D reconstruction or (self) calibration. A few novel algorithms illustrating some of these aspects, are described, especially concerning what we call calibration transfer, using fundamental matrices, and selfcalibration from plane homographies. 1.
3D reconstruction from image collections with a single known focal length
 In ICCV 2009
"... In this paper we aim at reconstructing 3D scenes from images with unknown focal lengths downloaded from photosharing websites such as Flickr. First we provide a minimal solution to finding the relative pose between a completely calibrated camera and a camera with an unknown focal length given six po ..."
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Cited by 8 (3 self)
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In this paper we aim at reconstructing 3D scenes from images with unknown focal lengths downloaded from photosharing websites such as Flickr. First we provide a minimal solution to finding the relative pose between a completely calibrated camera and a camera with an unknown focal length given six point correspondences. We show that this problem has up to nine solutions in general and present two efficient solvers to the problem. They are based on Gröbner basis, resp. on generalized eigenvalues, computation. We demonstrate by experiments with synthetic and real data that both solvers are correct, fast, numerically stable and work well even in some situations when the classical 6point algorithm fails, e.g. when optical axes of the cameras are parallel or intersecting. Based on this solution we present a new efficient method for largescale structure from motion from unordered data sets downloaded from the Internet. We show that this method can be effectively used to reconstruct 3D scenes from collection of images with very few (in principle single) images with known focal lengths 1. 1.
Robust focal length estimation by voting in multiview
"... scene reconstruction ..."
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Onesided Radial Fundamental Matrix Estimation
"... For modern consumer cameras often approximate calibration data is available, making applications such as 3D reconstruction or photo registration easier as compared to the pure uncalibrated setting. In this paper we address the setting with calibrateduncalibrated image pairs: for one image intrinsi ..."
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Cited by 1 (0 self)
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For modern consumer cameras often approximate calibration data is available, making applications such as 3D reconstruction or photo registration easier as compared to the pure uncalibrated setting. In this paper we address the setting with calibrateduncalibrated image pairs: for one image intrinsic parameters are assumed to be known, whereas the second view has unknown distortion and calibration parameters. This situation arises e.g. when one would like to register archive imagery to recently taken photos. A commonly adopted strategy for determining epipolar geometry is based on feature matching and minimal solvers inside a RANSAC framework. However, only very few existing solutions apply to the calibrateduncalibrated setting. We propose a simple and numerically stable twostep scheme to first estimate radial distortion parameters and subsequently the focal length using novel solvers. We demonstrate the performance on synthetic and real datasets. 1
4.2 Using Linear Calibration Objects............................... 3
"... pour obtenir le grade de Habilitation à diriger des Recherches de l’INSTITUT NATIONAL POLYTECHNIQUE DE GRENOBLE ..."
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pour obtenir le grade de Habilitation à diriger des Recherches de l’INSTITUT NATIONAL POLYTECHNIQUE DE GRENOBLE