Robust regression methods for computer vision: a review
International Journal of Computer Vision
Matching Two Perspective Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
A review of statistical data association for motion correspondence
International Journal of Computer Vision
Compact Representations of Videos Through Dominant and Multiple Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer and Robot Vision
Artificial Intelligence
Panoramic mosaics by manifold projection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Using geometric corners to build a 2D mosaic from a set of image
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Robust Computation and Parametrization of Multiple View Relations
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IMPSAC: Synthesis of Importance Sampling and Random Sample Consensus
IEEE Transactions on Pattern Analysis and Machine Intelligence
IMPSAC: Synthesis of Importance Sampling and Random Sample Consensus
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
A Compact and Retrieval-Oriented Video Representation Using Mosaics
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Image alignment and stitching: a tutorial
Foundations and Trends® in Computer Graphics and Vision
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The problem considered in this paper is that of estimating the projective transformation between two images in situations where the image motion is large and featurematching is not aided by a proximity heuristic. The overall algorithm designed is based on a multiresolution, multihypothesis scheme, and similarities between tracking and matching through mUltiple resolution levels are exploited. Two major tools are developed in this paper: (i) a Bayesian framework for incorporating similarity measures of feature correspondences in regression to specify the different levels of confidence in the correspondences; and (ii) a Bayesian version of RANSAC, which is able to utilise prior estimates and matching probabilities. The algorithm is tested on a number of real images with large image motion and promising results were obtained.