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Determining the Epipolar Geometry and its Uncertainty: A Review
 International Journal of Computer Vision
, 1998
"... Two images of a single scene/object are related by the epipolar geometry, which can be described by a 3×3 singular matrix called the essential matrix if images' internal parameters are known, or the fundamental matrix otherwise. It captures all geometric information contained in two i ..."
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Cited by 401 (9 self)
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Two images of a single scene/object are related by the epipolar geometry, which can be described by a 3&times;3 singular matrix called the essential matrix if images' internal parameters are known, or the fundamental matrix otherwise. It captures all geometric information contained in two images, and its determination is very important in many applications such as scene modeling and vehicle navigation. This paper gives an introduction to the epipolar geometry, and provides a complete review of the current techniques for estimating the fundamental matrix and its uncertainty. A wellfounded measure is proposed to compare these techniques. Projective reconstruction is also reviewed. The software which we have developed for this review is available on the Internet.
Automatic camera recovery for closed or open image sequences.
 In European conference on computer vision
, 1998
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3D Model Acquisition from Extended Image Sequences
, 1995
"... This paper describes the extraction of 3D geometrical data from image sequences, for the purpose of creating 3D models of objects in the world. The approach is uncalibrated  camera internal parameters and camera motion are not known or required. Processing an image sequence is underpinned by token ..."
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Cited by 236 (29 self)
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This paper describes the extraction of 3D geometrical data from image sequences, for the purpose of creating 3D models of objects in the world. The approach is uncalibrated  camera internal parameters and camera motion are not known or required. Processing an image sequence is underpinned by token correspondences between images. We utilise matching techniques which are both robust (detecting and discarding mismatches) and fully automatic. The matched tokens are used to compute 3D structure, which is initialised as it appears and then recursively updated over time. We describe a novel robust estimator of the trifocal tensor, based on a minimum number of token correspondences across an image triplet; and a novel tracking algorithm in which corners and line segments are matched over image triplets in an integrated framework. Experimental results are provided for a variety of scenes, including outdoor scenes taken with a handheld camcorder. Quantitative statistics are included to asses...
A SpaceSweep Approach to True Multi Image Matching
, 1995
"... The problem of determining feature correspondences across multiple views is considered. The term "true multiimage " matching is introduced to describe techniques that make full and efficient use of the geometric relationships between multiple images and the scene. A true multiimage techn ..."
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Cited by 221 (3 self)
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The problem of determining feature correspondences across multiple views is considered. The term "true multiimage " matching is introduced to describe techniques that make full and efficient use of the geometric relationships between multiple images and the scene. A true multiimage technique must generalize to any number of images, be of linear algorithmic complexity in the number of images, and use all the images in an equal manner. A new spacesweep approach to true multiimage matching is presented that simultaneously determines 2D feature correspondences and the 3D positions of feature points in the scene. The method is illustrated on a sevenimage matching example from the aerial image domain. 1
Sequential updating of projective and affine structure from motion
 International Journal of Computer Vision
, 1997
"... A structure from motion algorithm is described which recovers structure and camera position, modulo a projective ambiguity. Camera calibration is not required, and camera parameters such as focal length can be altered freely during motion. The structure is updated sequentially over an image sequenc ..."
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Cited by 161 (4 self)
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A structure from motion algorithm is described which recovers structure and camera position, modulo a projective ambiguity. Camera calibration is not required, and camera parameters such as focal length can be altered freely during motion. The structure is updated sequentially over an image sequence, in contrast to schemes which employ a batch process. A specialisation of the algorithm to recover structure and camera position modulo an affine transformation is described, together with a method to periodically update the affine coordinate frame to prevent drift over time. We describe the constraint used to obtain this specialisation. Structure is recovered from image corners detected and matched automatically and reliably in real image sequences. Results are shown for reference objects and indoor environments, and accuracy of recovered structure is fully evaluated and compared for a number of reconstruction schemes. A specific application of the work is demonstrated  affine structure is used to compute free space maps enabling navigation through unstructured environments and avoidance of obstacles. The path planning involves only affine constructions.
Occlusions and binocular stereo
 International Journal of Computer Vision
, 1996
"... A pair of frames eyes and an epipolar line in the left frame A matching space has elements M lr that decide if a feature at pixel l in the left epipolar line matches to a feature at pixel r in the right epipolar line Two dierent potentials that enforce piecew ..."
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Cited by 144 (5 self)
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A pair of frames eyes and an epipolar line in the left frame A matching space has elements M lr that decide if a feature at pixel l in the left epipolar line matches to a feature at pixel r in the right epipolar line Two dierent potentials that enforce piecewise smoothness It is desirable to use potentials Ux with large derivative where x eg x to avoid the creation of many small regions with small disparity changes Here x represents the disparity change between neighbouring pixel sites a A polyhedron shaded area with self occluding regions and with a discontinuity in the surfaceorientation at feature D and a depth discontinuity at feature C b A diagram of
Occlusions, discontinuities, and epipolar lines in stereo
 In European Conference on Computer Vision
, 1998
"... Abstract. Binocular stereo is the process of obtaining depth information from a pair of left and right views of a scene. We present a new approach to compute the disparity map by solving a global optimization problem that models occlusions, discontinuities, and epipolarline interactions. In the mod ..."
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Cited by 103 (8 self)
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Abstract. Binocular stereo is the process of obtaining depth information from a pair of left and right views of a scene. We present a new approach to compute the disparity map by solving a global optimization problem that models occlusions, discontinuities, and epipolarline interactions. In the model, geometric constraints require every disparity discontinuity along the epipolar lineinoneeyetoalways correspond to an occluded region in the other eye, while at the same time encouraging smoothness across epipolar lines. Smoothing coefficients are adjusted according to the edge and junction information. For some welldefined set of optimization functions, we can map the optimization problem to a maximumflow problem on a directed graph in a novel way, which enables us to obtain a global solution in a polynomial time. Experiments confirm the validity of this approach. 1
The problem of degeneracy in structure and motion recovery from uncalibrated image sequences
 International Journal of Computer Vision
, 1999
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Impsac: A synthesis of importance sampling and random sample consensus to effect multiscale image matching for small and wide baselines
 In ECCV2000
, 2000
"... The goal of this work is to obtain accurate matches and epipolar geometry between two images of the same scene, where the motion is unlikely to be smooth or known a priori. Once the matches and two view image relation have been recovered, they can be used for image compression, for building 3D model ..."
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Cited by 58 (1 self)
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The goal of this work is to obtain accurate matches and epipolar geometry between two images of the same scene, where the motion is unlikely to be smooth or known a priori. Once the matches and two view image relation have been recovered, they can be used for image compression, for building 3D models [3, 33, 35, 48], for object recognition [19], for extraction of images from databases [31]
Active visual navigation using nonmetric structure.
 In Proceedings of the 5th International Conference on Computer Vision,
, 1995
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