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Conference Paper Adaptive Estimation of Inlier and Outlier Threshold
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Authors
Jae-Yeong Lee, Wonpil Yu
Issue Date
2013-10
Citation
International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2013, pp.591-594
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/URAI.2013.6677398
Abstract
One of the main problems relating RANSAC estimation is to determine the inlier threshold adaptively depending on the variance of inliers. In this paper, we propose a novel method that estimates the inlier threshold adaptively from the observations, giving a threshold-free RANSAC. A minimum assumption of our method is that the lower bound of inlier ratio is known in advance and the variance of inliers follows Gaussian. We also describe a simple motion flow tracker as an application of the proposed method. In the experiment we show the effectiveness of the proposed method by comparing tracking performance with and without adaptive estimation of inlier threshold. © 2013 IEEE.
KSP Keywords
Lower bound, Tracking Performance, adaptive estimation, novel method