Robust Estimation of Camera Motion using Fuzzy Classification Method


The KIPS Transactions:PartB , Vol. 13, No. 7, pp. 671-678, Dec. 2006
10.3745/KIPSTB.2006.13.7.671,   PDF Download:

Abstract

In this paper, we propose a method for robustly estimating camera motion using fuzzy classification from the correspondences between two images. We use a RANSAC(Random Sample Consensus) algorithm to obtain accurate camera motion estimates in the presence of outliers. The drawback of RANSAC is that its performance depends on a prior knowledge of the outlier ratio. To resolve this problem, the proposed method classifies 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. The experimental results show that the proposed approach is very effective for computing a homography.


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Cite this article
[IEEE Style]
J. J. Lee, G. Y. Kim, H. I. Choi, "Robust Estimation of Camera Motion using Fuzzy Classification Method," The KIPS Transactions:PartB , vol. 13, no. 7, pp. 671-678, 2006. DOI: 10.3745/KIPSTB.2006.13.7.671.

[ACM Style]
Joong Jae Lee, Gye Young Kim, and Hyung Il Choi. 2006. Robust Estimation of Camera Motion using Fuzzy Classification Method. The KIPS Transactions:PartB , 13, 7, (2006), 671-678. DOI: 10.3745/KIPSTB.2006.13.7.671.