A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry

Zhang, Zhengyou; Deriche, Rachid; Faugeras, Olivier; Luong, Quang-Tuan

doi:10.1016/0004-3702(95)00022-4

Cited by 1,125 publications

(627 citation statements)

References 28 publications

Supporting

Mentioning

618

Contrasting

Unclassified

Order By: Relevance

“…4. Semilocal constraints have previously been used in [35], [36]. For each feature (interest point) in the database, the p closest features in the image are selected.…”

Section: Semilocal Constraintsmentioning

confidence: 99%

Local grayvalue invariants for image retrieval

Schmid¹,

Mohr²

1997

IEEE Trans. Pattern Anal. Machine Intell.

1,228

763

View full text Add to dashboard Cite

Abstract-This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows for efficient retrieval from a database of more than 1,000 images. Experimental results show correct retrieval in the case of partial visibility, similarity transformations, extraneous features, and small perspective deformations.

show abstract

“…4. Semilocal constraints have previously been used in [35], [36]. For each feature (interest point) in the database, the p closest features in the image are selected.…”

Section: Semilocal Constraintsmentioning

confidence: 99%

Local grayvalue invariants for image retrieval

Schmid¹,

Mohr²

1997

IEEE Trans. Pattern Anal. Machine Intell.

1,228

763

View full text Add to dashboard Cite

show abstract

“…From matched lines (n 1 , n 2 ) belonging to the same plane, a projective transformation H 21 exits, in such a way that n 2 =[H −1 21 ] T n 1 , being H 21 the 3×3 projective transformation of points x 2 = H 21 x 1 .…”

Section: Matches and Homographiesmentioning

confidence: 99%

“…Normally, it has been computed from corresponding points [1,10,11], using the epipolar constraint, which can be expressed as x T 2 F 21 x 1 = 0. However, the fundamental matrix is unstable when points lie close to planes [7].…”

Section: From Homographies To the Fundamental Matrixmentioning

confidence: 99%

See 1 more Smart Citation

From lines to epipoles through planes in two views

Sagüés

Murillo

Escudero

et al. 2006

Pattern Recognition

View full text Add to dashboard Cite

This paper addresses the computation of the fundamental matrix between two views, when camera motion and 3D structure are unknown, but planar surfaces can be assumed. We use line features which are automatically matched in two steps. Firstly, with image based parameters, a set of matches are obtained to secondly compute homographies, which allows to reject wrong ones, and to grow good matches in a final stage. The inclusion of projective transformations gives much better results to match features with short computing overload. When two or more planes are observed, different homographies can be computed, segmenting simultaneously the corresponding planar surfaces. These can be used to obtain the fundamental matrix, which gives constraints for the whole scene. The results show that the global process is robust enough, turning out stable and useful to obtain matches and epipolar geometry from lines in man made environments.

show abstract

“…3. Automatic detection of correspondences in image sequences, and elimination of outliers and false matches using the multifocal tensor relationships [14,18].…”

Section: Introductionmentioning

confidence: 99%

Dualizing Scene Reconstruction Algorithms

Hartley

Debunne

1998

3D Structure From Multiple Images of Large-Scale Environments

View full text Add to dashboard Cite

It has been known since the work of Carlsson [2] and Weinshall [17] that there is a dualization principle that allows one to interchange the role of points being viewed by several cameras and the camera centres themselves. In principle this implies the possibility of dualizing projective reconstruction algorithms to obtain new algorithms. In this paper, this theme is developed at a theoretical and algorithmic level. The nature of the duality mapping is explored and its application to reconstruction ambiguity is discussed. An explicit method for dualizing any projective reconstruction algorithm is given. At the practical implementation level, however, it is shown that there are difficulties which have so far defeated successful application of this dualization method to produce working algorithms.

show abstract

A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry

Cited by 1,125 publications

References 28 publications

Local grayvalue invariants for image retrieval

Local grayvalue invariants for image retrieval

From lines to epipoles through planes in two views

Dualizing Scene Reconstruction Algorithms

Contact Info

Product

Resources

About