• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

The development and comparison of robust methods for estimating the fundamental matrix”, (1997)

by P H S Torr, D W Murray
Venue:Int. J. Comput. Vision,
Add To MetaCart

Tools

Sorted by:
Results 1 - 10 of 266
Next 10 →

An Efficient Solution to the Five-Point Relative Pose Problem

by David Nister , 2004
"... An efficient algorithmic solution to the classical five-point relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degre ..."
Abstract - Cited by 484 (13 self) - Add to MetaCart
An efficient algorithmic solution to the classical five-point relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degree polynomial in closed form and subsequently finding its roots. It is the first algorithm well suited for numerical implementation that also corresponds to the inherent complexity of the problem. We investigate the numerical precision of the algorithm. We also study its performance under noise in minimal as well as over-determined cases. The performance is compared to that of the well known 8 and 7-point methods and a 6-point scheme. The algorithm is used in a robust hypothesize-and-test framework to estimate structure and motion in real-time with low delay. The real-time system uses solely visual input and has been demonstrated at major conferences.

MLESAC: A New Robust Estimator with Application to Estimating Image Geometry

by P. H. S. Torr, A. Zisserman - Computer Vision and Image Understanding , 2000
"... A new method is presented for robustly estimating multiple view relations from point correspondences. The method comprises two parts. The first is a new robust estimator MLESAC which is a generalization of the RANSAC estimator. It adopts the same sampling strategy as RANSAC to generate putative solu ..."
Abstract - Cited by 362 (10 self) - Add to MetaCart
A new method is presented for robustly estimating multiple view relations from point correspondences. The method comprises two parts. The first is a new robust estimator MLESAC which is a generalization of the RANSAC estimator. It adopts the same sampling strategy as RANSAC to generate putative solutions, but chooses the solution that maximizes the likelihood rather than just the number of inliers. The second part of the algorithm is a general purpose method for automatically parameterizing these relations, using the output of MLESAC. A difficulty with multiview image relations is that there are often nonlinear constraints between the parameters, making optimization a difficult task. The parameterization method overcomes the difficulty of nonlinear constraints and conducts a constrained optimization. The method is general and its use is illustrated for the estimation of fundamental matrices, image–image homographies, and quadratic transformations. Results are given for both synthetic and real images. It is demonstrated that the method gives results equal or superior to those of previous approaches. c ○ 2000 Academic Press 1.
(Show Context)

Citation Context

...ctivity). Hartley and Sturm [12] show how e, ˆx, and ˆx ′ may be found as the solution of a degree 6 polynomial. A computationally efficient first-order approximation to these is given in Torr et al. =-=[31, 34, 35]-=-. The above derivation assumes that the errors are Gaussian; often, however, features are mismatched and the error on m is not Gaussian. Thus the error is modeled as a mixture model of the Gaussian an...

Computer Vision: Algorithms and Applications

by Richard Szeliski , 2010
"... ..."
Abstract - Cited by 252 (2 self) - Add to MetaCart
Abstract not found

Automatic camera recovery for closed or open image sequences.

by A Fitzgibbon, A Zisserman - In European conference on computer vision , 1998
"... ..."
Abstract - Cited by 244 (17 self) - Add to MetaCart
Abstract not found

Robust parameter estimation in computer vision

by Charles V. Stewart - SIAM Reviews , 1999
"... Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation techni ..."
Abstract - Cited by 164 (10 self) - Add to MetaCart
Abstract. Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale 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 least-median of
(Show Context)

Citation Context

...ch ~ x i is found by searching an area of image 2 established by the range of scene depths and camera motions determined a priori. Within this area, which is sometimes as small as 30 pixels on a side =-=[76]-=-, but could be much larger depending on what restrictions are placed on camera motion, ~ x 0 i is the location of the image feature most similar to that of ~ x i , as decided by, for example, correlat...

Simultaneous object recognition and segmentation by image exploration

by Vittorio Ferrari, Tinne Tuytelaars, Luc Van Gool - 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. ..."
Abstract - Cited by 152 (20 self) - Add to MetaCart
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 non-rigid 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
(Show Context)

Citation Context

...f the paper, we refer to the current set of matches as the configuration Γ. How to proceed ? Global, robust geometry filtering methods, like detecting outliers to the epipolar geometry through RANSAC =-=[3]-=- fail, as they need a minimal amount of inliers of about 30% [8]. Initially, this may very well not be the case. Even if we could separate out the few correct matches, they would not be sufficient to ...

Viewpoint invariant texture matching and wide baseline stereo,”

by F Schaffalitzky, A Zisserman - in Proceedings of the 8th International Conference on Computer Vision, , 2001
"... ..."
Abstract - Cited by 109 (7 self) - Add to MetaCart
Abstract not found
(Show Context)

Citation Context

...e baseline stereo background For a significant variety of scene types the epipolar geometry can be computed automatically from two uncalibrated images provided the motion between the views is limited =-=[22, 26]-=-. The computation methods are based on robust statistics and proceed in three steps: interest points are detected independently in each image; putative point matches are then computed between the imag...

Graph Matching With a Dual-Step EM Algorithm

by Andrew D. J. Cross, Edwin R. Hancock - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1998
"... Abstract—This paper describes a new approach to matching geometric structure in 2D point-sets. The novel feature is to unify the tasks of estimating transformation geometry and identifying point-correspondence matches. Unification is realized by constructing a mixture model over the bipartite graph ..."
Abstract - Cited by 104 (6 self) - Add to MetaCart
Abstract—This paper describes a new approach to matching geometric structure in 2D point-sets. The novel feature is to unify the tasks of estimating transformation geometry and identifying point-correspondence matches. Unification is realized by constructing a mixture model over the bipartite graph representing the correspondence match and by affecting optimization using the EM algorithm. According to our EM framework, the probabilities of structural correspondence gate contributions to the expected likelihood function used to estimate maximum likelihood transformation parameters. These gating probabilities measure the consistency of the matched neighborhoods in the graphs. The recovery of transformational geometry and hard correspondence matches are interleaved and are realized by applying coupled update operations to the expected log-likelihood function. In this way, the two processes bootstrap one another. This provides a means of rejecting structural outliers. We evaluate the technique on two real-world problems. The first involves the matching of different perspective views of 3.5-inch floppy discs. The second example is furnished by the matching of a digital map against aerial images that are subject to severe barrel distortion due to a line-scan sampling process. We complement these experiments with a sensitivity study based on synthetic data.
(Show Context)

Citation Context

...a matrix representation of the transformation between image and model coordinate systems. Estimating the matrix requires a set of correspondence matches between features in the two coordinate systems =-=[37]-=-. In other words, the feature points must be labeled. Posed in this way, there is a basic chicken-and-egg problem. Before good correspondences can be estimated, there needs to be reasonable bounds on ...

Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint

by Yoram Leedan, Peter Meer - International Journal of Computer Vision
"... We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. ..."
Abstract - Cited by 97 (7 self) - Add to MetaCart
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix.

A quasi-dense approach to surface reconstruction from uncalibrated images

by Maxime Lhuillier, Long Quan, Senior Member - Transactions on Pattern Analysis and Machine Intelligence
"... Abstract—This paper proposes a quasi-dense approach to 3D surface model acquisition from uncalibrated images. First, correspondence information and geometry are computed based on new quasi-dense point features that are resampled subpixel points from a disparity map. The quasi-dense approach gives mo ..."
Abstract - Cited by 88 (20 self) - Add to MetaCart
Abstract—This paper proposes a quasi-dense approach to 3D surface model acquisition from uncalibrated images. First, correspondence information and geometry are computed based on new quasi-dense point features that are resampled subpixel points from a disparity map. The quasi-dense approach gives more robust and accurate geometry estimations than the standard sparse approach. The robustness is measured as the success rate of full automatic geometry estimation with all involved parameters fixed. The accuracy is measured by a fast gauge-free uncertainty estimation algorithm. The quasi-dense approach also works for more largely separated images than the sparse approach, therefore, it requires fewer images for modeling. More importantly, the quasidense approach delivers a high density of reconstructed 3D points on which a surface representation can be reconstructed. This fills the gap of insufficiency of the sparse approach for surface reconstruction, essential for modeling and visualization applications. Second, surface reconstruction methods from the given quasi-dense geometry are also developed. The algorithm optimizes new unified functionals integrating both 3D quasi-dense points and 2D image information, including silhouettes. Combining both 3D data and 2D images is more robust than the existing methods using only 2D information or only 3D data. An efficient bounded regularization method is proposed to implement the surface evolution by level-set methods. Its properties are discussed and proven for some cases. As a whole, a complete automatic and practical system of 3D modeling from raw images captured by hand-held cameras to surface representation is proposed. Extensive experiments demonstrate the superior performance of the quasi-dense approach with respect to the standard sparse approach in robustness, accuracy, and applicability. Index Terms—Three-dimensional reconstruction, surface reconstruction, structure from motion, 3D modeling, matching, uncertainty, variational calculus, level-set method. æ 1
(Show Context)

Citation Context

...-dense point is displayed with a small patch of texture. 4sThe standard sparse approach uses a robust statistical method to remove correspondence outliers by fitting the underlying fundamental matrix =-=[63, 54]-=- to the list of sparse point correspondences between the two images. Instead, we “densify” the correspondences by match propagation. We first sort this list of point correspondences using the correlat...

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University