Plane Detection in Point Cloud Data

Michael Ying Yang, Wolfgang Förstner

Research output: Working paperProfessional

200 Downloads (Pure)

Abstract

Plane detection is a prerequisite to a wide variety of vision tasks. RANdomSAmple Consensus (RANSAC) algorithm is widely used for plane detectionin point cloud data. Minimum description length (MDL) principle is used todeal with several competing hypothesis. This paper presents a new approachto the plane detection by integrating RANSAC and MDL. The method couldavoid detecting wrong planes due to the complex geometry of the 3D data.The paper tests the performance of proposed method on both synthetic andreal data.
Original languageUndefined
Place of PublicationBonn
PublisherUniversity of Bonn
Pages1-16
Number of pages16
Publication statusPublished - 2010

Publication series

NameIGG : Technical Report
PublisherInstitute of Geodesy and Geoinformation (IGG)
Volume1, 2010

Cite this

Yang, M. Y., & Förstner, W. (2010). Plane Detection in Point Cloud Data. (pp. 1-16). (IGG : Technical Report ; Vol. 1, 2010). Bonn: University of Bonn.
Yang, Michael Ying ; Förstner, Wolfgang. / Plane Detection in Point Cloud Data. Bonn : University of Bonn, 2010. pp. 1-16 (IGG : Technical Report ).
@techreport{dfc1d4a3c3c44da1867ced81d6c32a3b,
title = "Plane Detection in Point Cloud Data",
abstract = "Plane detection is a prerequisite to a wide variety of vision tasks. RANdomSAmple Consensus (RANSAC) algorithm is widely used for plane detectionin point cloud data. Minimum description length (MDL) principle is used todeal with several competing hypothesis. This paper presents a new approachto the plane detection by integrating RANSAC and MDL. The method couldavoid detecting wrong planes due to the complex geometry of the 3D data.The paper tests the performance of proposed method on both synthetic andreal data.",
author = "Yang, {Michael Ying} and Wolfgang F{\"o}rstner",
year = "2010",
language = "Undefined",
series = "IGG : Technical Report",
publisher = "University of Bonn",
pages = "1--16",
type = "WorkingPaper",
institution = "University of Bonn",

}

Yang, MY & Förstner, W 2010 'Plane Detection in Point Cloud Data' IGG : Technical Report , vol. 1, 2010, University of Bonn, Bonn, pp. 1-16.

Plane Detection in Point Cloud Data. / Yang, Michael Ying; Förstner, Wolfgang.

Bonn : University of Bonn, 2010. p. 1-16 (IGG : Technical Report ; Vol. 1, 2010).

Research output: Working paperProfessional

TY - UNPB

T1 - Plane Detection in Point Cloud Data

AU - Yang, Michael Ying

AU - Förstner, Wolfgang

PY - 2010

Y1 - 2010

N2 - Plane detection is a prerequisite to a wide variety of vision tasks. RANdomSAmple Consensus (RANSAC) algorithm is widely used for plane detectionin point cloud data. Minimum description length (MDL) principle is used todeal with several competing hypothesis. This paper presents a new approachto the plane detection by integrating RANSAC and MDL. The method couldavoid detecting wrong planes due to the complex geometry of the 3D data.The paper tests the performance of proposed method on both synthetic andreal data.

AB - Plane detection is a prerequisite to a wide variety of vision tasks. RANdomSAmple Consensus (RANSAC) algorithm is widely used for plane detectionin point cloud data. Minimum description length (MDL) principle is used todeal with several competing hypothesis. This paper presents a new approachto the plane detection by integrating RANSAC and MDL. The method couldavoid detecting wrong planes due to the complex geometry of the 3D data.The paper tests the performance of proposed method on both synthetic andreal data.

UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2010/scie/yang_pla.pdf

M3 - Working paper

T3 - IGG : Technical Report

SP - 1

EP - 16

BT - Plane Detection in Point Cloud Data

PB - University of Bonn

CY - Bonn

ER -

Yang MY, Förstner W. Plane Detection in Point Cloud Data. Bonn: University of Bonn. 2010, p. 1-16. (IGG : Technical Report ).