Olivier Faugeras. Three-Dimensional Computer Vision. MIT Press, Cambridge, MA, 1993. Home/Search Document Not in Database Summary Related Articles Check |
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Stratified Reconstruction from Multiple Images - David Jelinek Oct (Correct)
....of the optical center of the second camera is in the first image plane. More precisely, if the optical centers of the first and second camera are ( given by C and C2, we are looking for the point at which the line CC2 intersects the first camera s image plane. This is called the epipole [3] of the first camera and will be denoted e. Similarly, the epipole of the second camera (denoted e) is the point at which CC intersects the second camera s image plane. Suppose the first camera is located at the world origin with its axes coincident with the world axes. This is another way ....
Olivier Faugeras. Three-Dimensional Computer Vision. The MIT Press, Cam- bridge, Massachusetts, 1996. 19
Modeling and Rendering Architecture From Photographs - Debevec (1996) (348 citations) (Correct)
....relative to the camera center are known. However, the position of the camera in space (i.e. its translation and rotation with respect to world coordinates) is not necessarily known. An excellent presentation of the algebraic and matrix representations of 9 perspective cameras may be found in [13]. Considerable work has been done in both photogrammetry and computer vision to calibrate cameras and lenses for both their perspective intrinsic parameters and their distortion patterns. Some successful methods include [52] 12] and [11] While there has been recent progress in the use of ....
....between the two camera positions as well as the 3D locations of the points (up to a scale factor) Since then, the problem s mathematical and algorithmic aspects have been explored starting from the fundamental work of Ullman [54] and Longuet Higgins [25] in the early 1980s. Faugeras s book [13] overviews the state 10 of the art as of 1992. So far, a key realization has been that the recovery of structure is very sensitive to noise in image measurements when the translation between the available camera positions is small. Attention has turned to using more than two views with image ....
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Olivier Faugeras. Three-Dimensional Computer Vision. MIT Press, 1993.
A Two-Tiered Approach to Self-Localization - de Jong, Caarls, Bartelds, Jonker (2001) (6 citations) (Correct)
....perpendicular to it, # = # # 2, e find a number of candidate positions, hich follo from minima of a 1D matching cost function. We combine candidate positions on the two axes exhaustively, andg enerate the expected line pattern for each candidate poseusing standard imag e formation methods [6,8]. We then calculate the matching cost between the measured lines m i and the expected line pattern e j (c k ) for each candidate pose c k . For each measured line seg ent m i , we determine the distance D from its center point q i to the closest expected line, and combine these distances to gw a ....
Olivier FaugD7"9 "Three-dimensional Computer Vision", MIT Press, 1996.
A Two-Tiered Approach to Self-Localization - de Jong, Caarls, Bartelds, Jonker (2001) (6 citations) (Correct)
....perpendicular to it, # = # # 2, we find a number of candidate positions, which follow from minima of a 1D matching cost function. We combine candidate positions on the two axes exhaustively, and generate the expected line pattern for each candidate pose using standard image formation methods [6, 8]. We then calculate the matching cost between the measured lines m i and the expected line pattern e j (c k ) for each candidate pose c k . For each measured line segment m i , we determine the distance D from its center point q i to the closest expected line, and combine these distances to get a ....
Olivier FaugDI9" "Three-dimensional Computer Vision", MIT Press, 1996.
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Olivier Faugeras. Three-Dimensional Computer Vision. MIT Press, Cambridge, MA, 1993.
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Olivier Faugeras, Three-Dimensional Computer Vision, The MIT Press, Cambridge, Massachusetts, USA, 1993.
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Olivier Faugeras. Three-Dimensional Computer Vision. The MIT Press, 1993.
Robust Stereo and Adaptive Matching in Correlation Scal-Space - Menard (1997) (1 citation) (Correct)
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Olivier Faugeras. Three Dimensional Computer Vision. MIT Press, 1993.
Visual Servoing via Navigation Functions - Cowan, Weingarten, Koditschek (2002) (5 citations) (Correct)
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Olivier Faugeras, Three-Dimensional Computer Vision, MIT Press, London, England, 1993.
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Olivier Faugeras, Three dimensional computer vision, MIT Press, 1993.
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Olivier Faugeras. Three-Dimensional Computer Vision. Cambridge, MA, 1993. MIT Press.
Empirical Validation of a New Visual Servoing Strategy - Cowan, Weingarten, Koditschek (2001) (Correct)
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Olivier Faugeras. Three-Dimensional Computer Vision. MIT Press, London, England, 1993.
Combining Head-Mounted and Projector-Based Displays for.. - Kok-Lim Low Adrian (Correct)
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Olivier Faugeras. Three-Dimensional Computer Vision. MIT Press, 1993.
Calibrating a Structured Light System - McIvor, Valkenburg (1995) (2 citations) (Correct)
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Olivier Faugeras. Three-Dimensional Computer Vision. The MIT Press, 1993.
Accurate Correspondences From Epipolar Plane - Images Martin Matousek (Correct)
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Olivier Faugeras. Three-Dimensional Computer Vision. MIT Press, Cambridge, Massachusetts, 1993.
Visual Learning in Surveillance Systems - Makris (2001) (Correct)
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Olivier Faugeras, Three-Dimensional Computer Vision, A Geometric Viewpoint, The MIT Press, 1993.
Geometric 3D Comparison - an Application - Novotni, Klein (2001) (Correct)
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Olivier Faugeras. Three-Dimensional Computer Vision, a Geometric Viewpoint. MIT Press, 1993. 1
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