tailieunhanh - Báo cáo sinh học: " Research Article Two-Stage Outlier Elimination for Robust Curve and Surface Fitting"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Two-Stage Outlier Elimination for Robust Curve and Surface Fitting | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 154891 13 pages doi 2010 154891 Research Article Two-Stage Outlier Elimination for Robust Curve and Surface Fitting Jieqi Yu Haipeng Zheng Sanjeev R. Kulkarni and H. Vincent Poor Department of Electrical Engineering Princeton University Princeton NJ 08544 USA Correspondence should be addressed to Jieqi Yu jieqiyu@ Received 1 January 2010 Revised 25 April 2010 Accepted 7 June 2010 Academic Editor Ling Shao Copyright 2010 Jieqi Yu et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. An outlier elimination algorithm for curve surface fitting is proposed. This two-stage hybrid algorithm employs a proximitybased outlier detection algorithm followed by a model-based one. First a proximity graph is generated. Depending on the use of a hard soft threshold of the connectivity of observations two algorithms are developed one graph-component-based and the other eigenspace-based. Second a model-based algorithm taking the classification of inliers outliers of the first stage as its initial state iteratively refits and retests the observations with respect to the curve surface model until convergence. These two stages compensate for each other so that outliers of various types can be eliminated with a reasonable amount of computation. Compared to other algorithms this hybrid algorithm considerably improves the robustness of ellipse ellipsoid fitting for scenarios with large portions of outliers and high levels of inlier noise as demonstrated by extensive simulations. 1. Introduction Curve and surface fitting has a broad range of applications. For example in computer vision curves and surfaces are important geometric primitives and shape descriptors. As a result curve and surface fitting is .

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