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ICRA
2009
IEEE

An adaptive-scale robust estimator for motion estimation

13 years 1 months ago
An adaptive-scale robust estimator for motion estimation
Although RANSAC is the most widely used robust estimator in computer vision, it has certain limitations making it ineffective in some situations, such as the motion estimation problem, in which uncertainty on the image features changes according to the capturing conditions. The greatest problem is that the threshold used by RANSAC to detect inliers cannot be changed adaptively; instead it is fixed by the user. An adaptive scale algorithm must therefore be applied in such cases. In this paper, we propose a new adaptive scale robust estimator that adaptively finds the best solution with the best scale to fit the inliers, without the need for predefined information. Our new adaptive scale estimator matches the residual probability density from an estimate and the standard Gaussian probability density function to find the best inlier scale. Our algorithm is evaluated in several motion estimation experiments under varying conditions and the results are compared with several of the latest ad...
Trung Ngo Thanh, Hajime Nagahara, Ryusuke Sagawa,
Added 19 Feb 2011
Updated 19 Feb 2011
Type Journal
Year 2009
Where ICRA
Authors Trung Ngo Thanh, Hajime Nagahara, Ryusuke Sagawa, Yasuhiro Mukaigawa, Masahiko Yachida, Yasushi Yagi
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