The viewing graph

Levi, Netanel; Werman, Michael

doi:10.1109/cvpr.2003.1211398

Cited by 33 publications

(68 citation statements)

References 7 publications

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“…The epipole of the pure translational shot is computed using the eigenvalue decomposition of the matrix stacked by all lines connecting the corresponding points. In the case where two frames i and l might be far away and hence have no correspondences for the computation of the fundamental matrices, the viewing graph theory [15] is used for computing the fundamental matrices between the frames i and l, when there are two frames j and k which have overlap-8 ping areas with both i and l. In other words, the fundamental matrices inside two tri-views (i, j, k) and (j, k, l) are available.…”

Section: ×2mentioning

confidence: 99%

Video synchronization and its application to object transfer

Cao

Xiao³

et al. 2010

Image and Vision Computing

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Section: ×2mentioning

confidence: 99%

Video synchronization and its application to object transfer

Cao

Xiao³

et al. 2010

Image and Vision Computing

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“…As shown in [24] for example, the pairwise epipolar constraints among a set of images are redundant. We propose to exploit this redundancy by enforcing the corresponding geometric constraints.…”

Section: Filtering Out Inconsistent Projection Matricesmentioning

confidence: 99%

“…Then, the redundancy of multi-view epipolar geometry [24] is exploited to retain the consistent ones. The visual hull [3,21,23] of the observed solid is finally reconstructed from the recovered viewpoints.…”

Section: Introductionmentioning

confidence: 99%

Robust structure and motion from outlines of smooth curved surfaces

Furukawa

Sethi

Ponce

et al. 2006

IEEE Trans. Pattern Anal. Machine Intell.

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This article addresses the problem of estimating the motion of a camera as it observes the outline (or apparent contour) of a solid bounded by a smooth surface in successive image frames. In this context, the surface points that project onto the outline of an object depend on the viewpoint, and the only true correspondences between two outlines of the same object are the projections of frontier points where the viewing rays intersect in the tangent plane of the surface. In turn, the epipolar geometry is easily estimated once these correspondences have been identified. Given the apparent contours detected in an image sequence, a robust procedure based on RANSAC and a voting strategy is proposed to simultaneously estimate the camera configurations and a consistent set of frontier point projections by enforcing the redundancy of multi-view epipolar geometry. The proposed approach is, in principle, applicable to orthographic, weak-perspective and affine projection models. Experiments with nine real image sequences are presented for the orthographic projection case, including a quantitative comparison with the ground-truth data for the six datasets for which the latter information is available. Sample visual hulls have been computed from all image sequences for qualitative evaluation.

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“…As shown in [17] for example, the pairwise epipolar constraints among a set of images are redundant. We propose in this section to exploit this redundancy by enforcing the corresponding geometric constraints during matching.…”

Section: Enforcing Geometric Consistencymentioning

confidence: 99%

“…An algorithm for identifying geometrically-consistent frontier point candidates while estimating the cameras' projection matrices is presented. This algorithm uses the signature representation of the dual of image silhouettes, proposed in [1] in the object recognition context, to identify promising correspondences, and it exploits the redundancy of multiple epipolar geometries [17] to retain the consistent ones. The visual hull [3,16] of the observed solid is finally reconstructed from the recovered viewpoints.…”

Section: Introductionmentioning

confidence: 99%

Structure and Motion from Images of Smooth Textureless Objects

Furukawa

Sethi

Ponce

et al. 2004

Lecture Notes in Computer Science

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Abstract. This paper addresses the problem of estimating the 3D shape of a smooth textureless solid from multiple images acquired under orthographic projection from unknown and unconstrained viewpoints. In this setting, the only reliable image features are the object's silhouettes, and the only true stereo correspondence between pairs of silhouettes are the frontier points where two viewing rays intersect in the tangent plane of the surface. An algorithm for identifying geometrically-consistent frontier points candidates while estimating the cameras' projection matrices is presented. This algorithm uses the signature representation of the dual of image silhouettes to identify promising correspondences, and it exploits the redundancy of multiple epipolar geometries to retain the consistent ones. The visual hull of the observed solid is finally reconstructed from the recovered viewpoints. The proposed approach has been implemented, and experiments with six real image sequences are presented, including a comparison between ground-truth and recovered camera configurations, and sample visual hulls computed by the algorithm.

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The viewing graph

Cited by 33 publications

References 7 publications

Video synchronization and its application to object transfer

Video synchronization and its application to object transfer

Robust structure and motion from outlines of smooth curved surfaces

Structure and Motion from Images of Smooth Textureless Objects

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