Results 1  10
of
66
Automatic Line Matching across Views
 In Proc. CVPR
, 1997
"... This paper presents a new method for matching individual line segments between images. The method uses both greylevel information and the multiple view geometric relations between the images. For image pairs epipolar geometry facilitates the computation of a crosscorrelation based matching score fo ..."
Abstract

Cited by 78 (8 self)
 Add to MetaCart
(Show Context)
This paper presents a new method for matching individual line segments between images. The method uses both greylevel information and the multiple view geometric relations between the images. For image pairs epipolar geometry facilitates the computation of a crosscorrelation based matching score for putative line correspondences. For image triplets crosscorrelation matching scores are used in conjunction with line transfer based on the trifocal geometry. Algorithms are developed for both short and long range motion. In the case of long range motion the algorithm involves evaluating a one parameter family of plane induced homographies. The algorithms are robust to deficiencies in the line segment extraction and partial occlusion. Experimental results are given for image pairs and triplets, for varying motions between views, and for different scene types. The three view algorithm eliminates all mismatches. 1.
Real time correlationbased stereo: algorithm, implementations and applications
, 1993
"... ..."
(Show Context)
The Geometry and Matching of Lines and Curves Over Multiple Views
"... This paper describes the geometry of imaged curves in two and three views. Multiview relationships are developed for lines, conics and nonalgebraic curves. The new relationships focus on determining the plane of the curve in a projective reconstruction, and in particular using the homography in ..."
Abstract

Cited by 45 (1 self)
 Add to MetaCart
This paper describes the geometry of imaged curves in two and three views. Multiview relationships are developed for lines, conics and nonalgebraic curves. The new relationships focus on determining the plane of the curve in a projective reconstruction, and in particular using the homography induced by this plane for transfer from one image to another. It is shown that given the fundamental matrix between two views, and images of the curve in each view, then the plane of a conic may be determined up to a two fold ambiguity, but local curvature of a curve uniquely determines the plane. It is then shown that given the trifocal tensor between three views, this plane defines a homography map which may be used to transfer a conic or the curvature from two views to a third. Simple expressions are developed for the plane and homography in each case.
A progressive scheme for stereo matching
 LNCS 2018: 3D Structure from Images  SMILE 2000
, 2001
"... Bruteforce dense matching is usually not satisfactory because the same search range is used for the entire image, yielding potentially many false matches. In this paper, we propose a progressive scheme for stereo matching which uses two fundamental concepts: the disparity gradient limit principle a ..."
Abstract

Cited by 25 (1 self)
 Add to MetaCart
(Show Context)
Bruteforce dense matching is usually not satisfactory because the same search range is used for the entire image, yielding potentially many false matches. In this paper, we propose a progressive scheme for stereo matching which uses two fundamental concepts: the disparity gradient limit principle and the least commitment strategy. The first states that the disparity should vary smoothly almost everywhere, and the disparity gradient should not exceed a certain limit. The second states that we should first select only the most reliable matches and therefore postpone unreliable decisions until enough confidence is accumulated. Our technique starts with a few reliable point matches obtained automatically via feature correspondence or through user input. New matches are progressively added during an iterative matching process. At each stage, the current reliable matches constrain the search range for their neighbors according to the disparity gradient limit, thereby reducing potential matching ambiguities of those neighbors. Only unambiguous matches are selected and added to the set of reliable matches in accordance with the least commitment strategy. In addition, a correlation match measure that allows rotation of the match template is used to provide a more robust estimate. The entire process is cast within a Bayesian inference framework. Experimental results illustrate the robustness of our proposed dense stereo matching approach.
Using Local Planar Geometric Invariants to Match and Model Images of Line Segments
 J. OF COMP. VISION AND IMAGE UNDERST
, 1998
"... Image matching consists of finding features in different images that represent the same feature of the observed scene. It is a basic process in vision whenever several images are used. This paper describes a matching algorithm for lines segments in two images. The key idea of the algorithm is to ass ..."
Abstract

Cited by 20 (4 self)
 Add to MetaCart
(Show Context)
Image matching consists of finding features in different images that represent the same feature of the observed scene. It is a basic process in vision whenever several images are used. This paper describes a matching algorithm for lines segments in two images. The key idea of the algorithm is to assume that the apparent motion between the two images can be approximated by a planar geometric transformation (a similarity or an affine transformation) and to compute such an approximation. Under such an assumption, local planar invariants related the kind of transformation used as approximation, should have the same value in both images. Such invariants are computed for simple segment configurations in both images and matched according to their values. A global constraint is added to insure a global coherency between all the possible matches: all the local matches must define approximately the same geometric transformation between the two images. These first matches are verified and complet...
Symmetric stereo with multiple windowing
 International Journal of Pattern Recognition and Artificial Intelligence
, 2000
"... We present a new, efficient stereo algorithm addressing robust disparity estimation in the presence of occlusions. The algorithm is an adaptive, multiwindow scheme using left– right consistency to compute disparity and its associated uncertainty. We demonstrate and discuss performances with both syn ..."
Abstract

Cited by 19 (2 self)
 Add to MetaCart
(Show Context)
We present a new, efficient stereo algorithm addressing robust disparity estimation in the presence of occlusions. The algorithm is an adaptive, multiwindow scheme using left– right consistency to compute disparity and its associated uncertainty. We demonstrate and discuss performances with both synthetic and real stereo pairs, and show how our results improve on those of closely related techniques for both accuracy and efficiency.
Knowledgebased image analysis for 3D edge extraction and road reconstruction
 International Archives of Photogrammetry and Remote Sensing
, 2000
"... Road network extraction from aerial images has received attention in photogrammetry and computer vision for decades. We present a concept for road network reconstruction from aerial images using knowledgebased image analysis. In contrast to other approaches, the proposed approach uses multiple cues ..."
Abstract

Cited by 19 (12 self)
 Add to MetaCart
(Show Context)
Road network extraction from aerial images has received attention in photogrammetry and computer vision for decades. We present a concept for road network reconstruction from aerial images using knowledgebased image analysis. In contrast to other approaches, the proposed approach uses multiple cues about the object existence, employs existing knowledge, rules and models, and treats each road subclass differently to increase success rate and reliability of the results. Finding 3D edges on the road and especially the road borders is a crucial component of our procedure and is the focus of this paper. We developed an algorithm for automatically matching line segments across images. The algorithm exploits line geometrical and photometrical attributes and line geometrical structures. A framework to integrate these information sources using probability relaxation is developed and implemented to deliver locally consistent matches. Results of straight line matching are presented and future work is discussed. 1
Stereo by Twolevel Dynamic Programming
 In 9th Int. Joint Conf. Artificial Intelligence
, 1985
"... This paper presents a stereo algorithm using dynamic programming technique. The stereo matching problem, that is, obtaining a correspondence between right and left images, can be cast as a search problem. When a pair of stereo images is rectified, pairs of corresponding points can be searched for wi ..."
Abstract

Cited by 16 (0 self)
 Add to MetaCart
This paper presents a stereo algorithm using dynamic programming technique. The stereo matching problem, that is, obtaining a correspondence between right and left images, can be cast as a search problem. When a pair of stereo images is rectified, pairs of corresponding points can be searched for within the same scanlines. We call this search intrascanline search. This intrascanline search can be treated as the problem of finding a matching path on a two dimensional (2D) search plane whose axes are the right and left scanlines. Vertically connected edges in the images provide consistency constraints across the 2D search planes. Interscanline search in a threedimensional (3D) search space, which is a stack of the 2D search planes, is needed to utilize this constraint. Our stereo matching algorithm uses edgedelimited intervals as elements to be matched, and employs the above mentioned two searches: one is interscanline search for possible correspondences of connected edges in right and left images and the other is intrascanline search for correspondences of edgedelimited intervals on each scanline pair. Dynamic programming is used for both searches which proceed simultaneously in two levels: the former supplies the consistency constraints to the latter while the latter supplies the matching score to the former. An intervalbased similarity metric is used to compute the score. 1.
Mobile Robot Navigation And Scene Modeling Using Stereo FishEye Lens System
 MACHINE VISION AND APPLICATIONS 10
, 1997
"... We present an autonomous mobile robot navigation system using stereo fisheye lenses for navigation in an indoor structured environment, and for generating a model of the imaged scene. The system estimates the threedimensional (3D) position of significant features in the scene, and by estimating it ..."
Abstract

Cited by 14 (0 self)
 Add to MetaCart
We present an autonomous mobile robot navigation system using stereo fisheye lenses for navigation in an indoor structured environment, and for generating a model of the imaged scene. The system estimates the threedimensional (3D) position of significant features in the scene, and by estimating its relative position, navigates through narrow passages and makes turns at corridor ends. Fisheye lenses are used to provide a large field of view, which helps in imaging objects close to the robot and in making smooth transitions in the direction of motion. Calibration is performed for the lenscamera setup and the distortion is corrected to obtain accurate quantitative measurements. A vision based algorithm that uses the vanishing points of extracted segments from a scene in a few 3D orientations provides an accurate estimate of the robot orientation. This is used, in addition to 3D recovery via stereo correspondence, to maintain the robot motion in a purely translational path as well as to r...
Stereo Without Search
 EUROPEAN CONFERENCE ON COMPUTER VISION (ECCV)
, 1996
"... In its traditional formulation, stereo correspondence involves both searching and selecting. Given a feature in one scanline, the corresponding scanline in the other image is searched for the positions of similar features. Often more than one candidate is found, and the correct one must be selec ..."
Abstract

Cited by 13 (2 self)
 Add to MetaCart
In its traditional formulation, stereo correspondence involves both searching and selecting. Given a feature in one scanline, the corresponding scanline in the other image is searched for the positions of similar features. Often more than one candidate is found, and the correct one must be selected. The problem of selection is unavoidable because different features look similar to each other. Search, on the other hand, is not inherent in the correspondence problem. We propose a representation of scanlines, called intrinsic curves, that avoids search over different disparities. The idea is to represent scanlines by means of local descriptor vectors, without regard for where in the image a descriptor is computed, but without losing information about the contiguity of image points. In fact, intrinsic curves are the paths that the descriptor vector traverses as an image scanline is traversed from left to right. Because the...