A New Approach to Robust Estimation of Parametric Structures. Academic Article

abstract

• Most robust estimators require tuning the parameters of the algorithm for the particular application, a bottleneck for practical applications. The paper presents the multiple input structures with robust estimator (MISRE), where each structure, inlier or outlier, is processed independently. The same two constants are used to find the scale estimates over expansions for each structure. The inlier/outlier classification is straightforward since the data is processed and ordered with the relevant inlier structures listed first. If the inlier noises are similar, MISRE's performance is equivalent to RANSAC-type algorithms. MISRE still returns the correct inlier estimates when inlier noises are very different, while RANSAC-type algorithms do not perform as well. MISRE's failures are gradual when too many outliers are present, beginning with the least significant inlier structure. Examples from 2D images and 3D point clouds illustrate the estimation.

authors

• Meer, Jonathan

published proceedings

• IEEE Trans Pattern Anal Mach Intell

author list (cited authors)

• Yang, X., Meer, P., & Meer, J.

citation count

• 4

complete list of authors

• Yang, Xiang||Meer, Peter||Meer, Jonathan

publication date

• November 2021

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Pattern Analysis and Machine Intelligence  Journal

keywords

• Complexity Theory
• Covariance Matrices
• Density Based Classification
• Estimation
• Linear Programming
• Robustness
• Scale Estimation
• Structures Segmentation
• Three-dimensional Displays
• Two Dimensional Displays

Digital Object Identifier (DOI)

• 10.1109/TPAMI.2020.2994190

start page

• 3754

end page

• 3769

volume

• 43

issue

• 11

URL

• http://dx.doi.org/10.1109/tpami.2020.2994190