| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
P.~H.~S. Torr and A. Zisserman
ABSTRACT
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 to maximize the likelihood rather than just the number of inliers. The second part to the algorithm is a general purpose method for automatically parametrizing these relations, using the output of MLESAC. A difficulty with multi view image relations is that there are often non-linear constraints between the parameters, making optimization a difficult task. The parametrization method overcomes the difficulty of non-linear 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 previous approaches. |
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