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545
On the geometry and algebra of the point and line correspondences between N images
, 1995
"... We explore the geometric and algebraic relations that exist between correspondences of points and lines in an arbitrary number of images. We propose to use the formalism of the GrassmannCayley algebra as the simplest way to make both geometric and algebraic statements in a very synthetic and effect ..."
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Cited by 164 (7 self)
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We explore the geometric and algebraic relations that exist between correspondences of points and lines in an arbitrary number of images. We propose to use the formalism of the GrassmannCayley algebra as the simplest way to make both geometric and algebraic statements in a very synthetic and effective way (i.e. allowing actual computation if needed). We have a fairly complete picture of the situation in the case of points: there are only three types of algebraic relations which are satisfied by the coordinates of the images of a 3D point: bilinear relations arising when we consider pairs of images among the N and which are the wellknown epipolar constraints, trilinear relations arising when we consider triples of images among the N , and quadrilinear relations arising when we consider fourtuples of images among the N . In the case of lines, we show how the traditional perspective projection equation can be suitably generalized and that in the case of three images there exist two in...
Robust parameter estimation in computer vision
 SIAM Reviews
, 1999
"... Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite smallscale noise in the data, occasional largescale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation techni ..."
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Cited by 162 (10 self)
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Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite smallscale noise in the data, occasional largescale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation techniques, some borrowed from the statistics literature and others described in the computer vision literature, have been used in solving these parameter estimation problems. Ideally, these techniques should effectively ignore the outliers and measurements from other populations, treating them as outliers, when estimating the parameters of a single population. Two frequently used techniques are leastmedian of
Wide baseline stereo matching
 Sixth International Conference on Computer Vision
, 2004
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In Defence of the 8point Algorithm
"... The fundamental matrix is a basic tool in the analysis of scenes taken with two uncalibrated cameras, and the 8point algoritm is a frequent#e cit#3 met#9 d for comput#10 t he fundament al ma t# ix from a set of 8 or more point mat ches. It hast he advant age of simplicit y of implement at ion. The ..."
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Cited by 159 (3 self)
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The fundamental matrix is a basic tool in the analysis of scenes taken with two uncalibrated cameras, and the 8point algoritm is a frequent#e cit#3 met#9 d for comput#10 t he fundament al ma t# ix from a set of 8 or more point mat ches. It hast he advant age of simplicit y of implement at ion. The prevailing view is, however,t#(9 it isext#3791( suscept#43 t o noise and hence virtually useless for most purposes. This paper challengest#en view, by showing t#ng by precedingt he algorit hm wit h a very simple normalizat ion(t ranslat ion and scaling) oft he coordinat es oft he mat ched point#( result# are obt# ined comparable wit# t he best it## at ive algorit#209 This improved performance is just#690 byt#1082 and verified byext#259( e experiment s on real images.
Invariant Features from Interest Point Groups
 In British Machine Vision Conference
, 2002
"... This paper approaches the problem of finding correspondences between images in which there are large changes in viewpoint, scale and illumination. Recent work has shown that scalespace `interest points' may be found with good repeatability in spite of such changes. Furthermore, the high entrop ..."
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Cited by 153 (2 self)
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This paper approaches the problem of finding correspondences between images in which there are large changes in viewpoint, scale and illumination. Recent work has shown that scalespace `interest points' may be found with good repeatability in spite of such changes. Furthermore, the high entropy of the surrounding image regions means that local descriptors are highly discriminative for matching. For descriptors at interest points to be robustly matched between images, they must be as far as possible invariant to the imaging process.
Local greyvalue invariants for image retrieval
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1997
"... Abstract  This paper addresses the problem of retrieving images from large image databases. The method is based on local greyvalue invariants which are computed at automatically detected interest points. Avoting algorithm and semilocal constraints make retrieval possible. Indexing allows for e cie ..."
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Cited by 151 (5 self)
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Abstract  This paper addresses the problem of retrieving images from large image databases. The method is based on local greyvalue invariants which are computed at automatically detected interest points. Avoting algorithm and semilocal constraints make retrieval possible. Indexing allows for e cient retrieval from a database of more than 1000 images. Experimental results show correct retrieval in the case of partial visibility, similarity transformations, extraneous features, and small perspective deformations.
Simultaneous object recognition and segmentation by image exploration
 In Proceedings of the European Conference on Computer Vision
, 2004
"... Abstract. Methods based on local, viewpoint invariant features have proven capable of recognizing objects in spite of viewpoint changes, occlusion and clutter. However, these approaches fail when these factors are too strong, due to the limited repeatability and discriminative power of the features. ..."
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Cited by 151 (20 self)
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Abstract. Methods based on local, viewpoint invariant features have proven capable of recognizing objects in spite of viewpoint changes, occlusion and clutter. However, these approaches fail when these factors are too strong, due to the limited repeatability and discriminative power of the features. As additional shortcomings, the objects need to be rigid and only their approximate location is found. We present an object recognition approach which overcomes these limitations. An initial set of feature correspondences is first generated. The method anchors on it and then gradually explores the surrounding area, trying to construct more and more matching features, increasingly farther from the initial ones. The resulting process covers the object with matches, and simultaneously separates the correct matches from the wrong ones. Hence, recognition and segmentation are achieved at the same time. Only very few correct initial matches suffice for reliable recognition. Experimental results on still images and television news broadcasts demonstrate the stronger power of the presented method in dealing with extensive clutter, dominant occlusion, large scale and viewpoint changes. Moreover nonrigid deformations are explicitly taken into account, and the approximative contours of the object are produced. The approach can extend any viewpoint invariant feature extractor. 1
Monocular modelbased 3d tracking of rigid objects: A survey
 In Foundations and Trends in Computer Graphics and Vision
, 2005
"... Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Augmented Reality systems that require realtime registration of the object to be augmented, and head tracking systems that sophisticated interfaces can use. Computer ..."
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Cited by 142 (4 self)
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Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Augmented Reality systems that require realtime registration of the object to be augmented, and head tracking systems that sophisticated interfaces can use. Computer Vision offers solutions that are cheap, practical and noninvasive. This survey reviews the different techniques and approaches that have been developed by industry and research. First, important mathematical tools are introduced: Camera representation, robust estimation and uncertainty estimation. Then a comprehensive study is given of the numerous approaches developed by the Augmented Reality and Robotics communities, beginning with those that are based on point or planar fiducial marks and moving on to those that avoid the need to engineer the environment by relying on natural features such as edges, texture or interest. Recent advances that avoid manual initialization and failures due to fast motion are also presented. The survery concludes with the different possible choices that should be made when implementing a 3D tracking system and a discussion of the future of visionbased 3D tracking. Because it encompasses many computer vision techniques from lowlevel vision to 3D geometry and includes a comprehensive study of the massive literature on the subject, this survey should be the handbook of the student, the researcher, or the engineer who wants to implement a 3D tracking system. 1
SBA: a software package for generic sparse bundle adjustment
 ACM Transactions on Mathematical Software
, 2009
"... Foundation for Research and Technology—Hellas ..."
Faugeras O. D.: Selfcalibration of a moving camera from point correspondences and fundamental matrices
 International Journal of Computer Vision
, 1997
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