Robust estimation of camera homography using fuzzy RANSAC

Authors:
Joong Jae Lee;Gyeyoung Kim
Affiliations:
Center for Cognitive Robotics Reseach, Korea Institute of Science and Technology, Seoul, Korea;School of Computer Science, Soongsil University, Seoul, Korea
Venue:
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Year:
2007

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Abstract

In this paper, we propose a method for robustly estimating camera homography using fuzzy RANSAC from the correspondences between consecutive two images. We use a fuzzified version of the original RANSAC algorithm to obtain accurate camera homography in the presence of outliers. The drawback of RANSAC is that its performance depends on a prior knowledge of the outlier scale. To resolve this problem, the proposed method classifies all samples into three classes (good sample set, bad sample set and vague sample set) using fuzzy classification. It then improves classification accuracy omitting outliers by iteratively sampling in only good sample set. Experimental results show the robustness of the proposed approach for computing a homography on real image sequence.