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Sample Consensus Fitting of Bivariate Polynomials for Initializing EM-based Modeling of Smooth 3D Surfaces

Nissler, Christian and Marton, Zoltan Csaba and Suppa, Michael (2013) Sample Consensus Fitting of Bivariate Polynomials for Initializing EM-based Modeling of Smooth 3D Surfaces. In: IEEE International Conference on Intelligent Robots and Systems. International Conference on Intelligent Robots and Systems, 3.-8. Nov. 2013, Tokio, Japan.

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Abstract

This paper presents a method for finding the largest, connected, smooth surface in noisy depth images. The formulation of the fitting in a Sample Consensus way allows the use of RANSAC (or any other similar estimator), and makes the method tolerant to low percentage of inliers in the input. Therefore it can be used to simultaneously segment and model the surface of interest. This is important in applications like analyzing physical properties of Carbon-fiber-reinforced polymer (CFRP) structures. Using bivariate polynomials for modeling turns out to be advantageous, allowing to capture the variations along the two directions on the surface. However, fitting them efficiently using RANSAC is not straightforward. We present the necessary preand post-processing, distance and normal direction checks, and degree optimization (lowering the order of the polynomial), and evaluate how these improve results. Finally, to improve the initial estimate provided by RANSAC, an Expectation Maximization approach is employed, converging to the best solution. The method was tested on high-quality data and as well on real-world scenes captured by a RGB-D camera. We will publish the method as part of the Point Cloud Library.

Item URL in elib:https://elib.dlr.de/87117/
Document Type:Conference or Workshop Item (Speech)
Title:Sample Consensus Fitting of Bivariate Polynomials for Initializing EM-based Modeling of Smooth 3D Surfaces
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Nissler, ChristianChristian.Nissler (at) dlr.deUNSPECIFIED
Marton, Zoltan Csabazoltan.marton (at) dlr.deUNSPECIFIED
Suppa, MichaelMichael.Suppa (at) dlr.deUNSPECIFIED
Date:November 2013
Journal or Publication Title:IEEE International Conference on Intelligent Robots and Systems
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Series Name:Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems
Status:Published
Keywords:Surface Estimation, 3D fitting, 3D modeling with polynomials, RANSAC, Expectation Maximization, Segmentation
Event Title:International Conference on Intelligent Robots and Systems
Event Location:Tokio, Japan
Event Type:international Conference
Event Dates:3.-8. Nov. 2013
Organizer:IEEE/RSJ
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Multisensorielle Weltmodellierung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Nissler, Christian
Deposited On:20 Dec 2013 14:14
Last Modified:31 Jul 2019 19:44

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