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Characterizing the Uncertainty of the Fundamental Matrix
 Computer Vision and Image Understanding
, 1995
"... This paper deals with the analysis of the uncertainty of the fundamental matrix. The basic idea is to compute the fundamental matrix and its uncertainty in the same time. We shall show two different methods. The first one is a statistical approach. As in all statistical methods the precision of the ..."
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Cited by 60 (5 self)
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This paper deals with the analysis of the uncertainty of the fundamental matrix. The basic idea is to compute the fundamental matrix and its uncertainty in the same time. We shall show two different methods. The first one is a statistical approach. As in all statistical methods the precision
The development and comparison of robust methods for estimating the fundamental matrix
 International Journal of Computer Vision
, 1997
"... Abstract. This paper has two goals. The first is to develop a variety of robust methods for the computation of the Fundamental Matrix, the calibrationfree representation of camera motion. The methods are drawn from the principal categories of robust estimators, viz. case deletion diagnostics, Mest ..."
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Cited by 263 (10 self)
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Abstract. This paper has two goals. The first is to develop a variety of robust methods for the computation of the Fundamental Matrix, the calibrationfree representation of camera motion. The methods are drawn from the principal categories of robust estimators, viz. case deletion diagnostics, M
The Fundamental matrix: theory, algorithms, and stability analysis
 International Journal of Computer Vision
, 1995
"... In this paper we analyze in some detail the geometry of a pair of cameras, i.e. a stereo rig. Contrarily to what has been done in the past and is still done currently, for example in stereo or motion analysis, we do not assume that the intrinsic parameters of the cameras are known (coordinates of th ..."
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Cited by 273 (13 self)
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for establishing correspondences between two pairs of images. This information is fundamentally projective and is hidden in a confusing manner in the commonly used formalism of the Essential matrix introduced by LonguetHiggins [40]. This paper clarifies the projective nature of the correspondence problem
collineations and the fundamental matrix
 Proc. 10th British Machine Vision Conference
, 1999
"... Scene geometry can be inferred from point correspondences between two images. The inference process includes the selection of a model. Four models are considered: background (or null), collineation, affine fundamental matrix and fundamental matrix. It is shown how Minimum Description Length (MDL) ca ..."
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Cited by 9 (0 self)
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Scene geometry can be inferred from point correspondences between two images. The inference process includes the selection of a model. Four models are considered: background (or null), collineation, affine fundamental matrix and fundamental matrix. It is shown how Minimum Description Length (MDL
On the Direct Estimation of the Fundamental Matrix
"... The fundamental matrix is a central construct in the analysis of images captured from a pair of cameras and many featurebased methods have been proposed for its computation. In this paper, we propose a direct method for estimating the fundamental matrix where the motion between the frames is small ..."
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Cited by 4 (0 self)
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The fundamental matrix is a central construct in the analysis of images captured from a pair of cameras and many featurebased methods have been proposed for its computation. In this paper, we propose a direct method for estimating the fundamental matrix where the motion between the frames is small
Compact fundamental matrix computation
 Proc. 3rd Pacific Rim Symp. Image and Video Technology
, 2009
"... Abstract. A very compact algorithm is presented for fundamental matrix computation from point correspondences over two images. The computation is based on the strict maximum likelihood (ML) principle, minimizing the reprojection error. The rank constraint is incorporated by the EFNS procedure. Altho ..."
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Cited by 6 (4 self)
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Abstract. A very compact algorithm is presented for fundamental matrix computation from point correspondences over two images. The computation is based on the strict maximum likelihood (ML) principle, minimizing the reprojection error. The rank constraint is incorporated by the EFNS procedure
SelfCalibration and the Fundamental Matrix
"... ra using only the information available in the images taken by that camera. No calibration frame or known object is needed: the only requirement is that there is a static object in the scene, and the camera moves around taking images. Thus selfcalibration is 1 ideal for a mobile camera, such as a ..."
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camera mounted on a mobile robot. The actual camera movement itself does not need to be known. The geometric information that relates two different viewpoints of the same scene is entirely contained in a mathematical construct known as the fundamental matrix. The two viewpoints could be a stereo pair
Tensor Embedding of the Fundamental Matrix
 In Proc. of postECCV SMILEâ€™98, volume Springer LNCS 1506
, 1998
"... We revisit the bilinear matching constraint between two perspective views of a 3D scene. Our objective is to represent the constraint in the same manner and form as the trilinear constraint among three views. The motivation is to establish a common terminology that bridges between the fundamental ma ..."
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Cited by 6 (0 self)
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We revisit the bilinear matching constraint between two perspective views of a 3D scene. Our objective is to represent the constraint in the same manner and form as the trilinear constraint among three views. The motivation is to establish a common terminology that bridges between the fundamental
BELLAVIA, TEGOLO: NORANSAC FOR FUNDAMENTAL MATRIX ESTIMATION 1
"... noRANSAC for fundamental matrix estimation ..."
Projective rectification from the fundamental matrix
 Image and Vision Computing
, 2005
"... This paper describes a direct, selfcontained method for planar image rectification of stereo pairs. The method is based solely on an examination of the Fundamental matrix, where an improved method is given for the derivation of two projective transformations that horizontally align all the epipolar ..."
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Cited by 24 (3 self)
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This paper describes a direct, selfcontained method for planar image rectification of stereo pairs. The method is based solely on an examination of the Fundamental matrix, where an improved method is given for the derivation of two projective transformations that horizontally align all
Results 1  10
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