An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings

Fatemeh Hamid-Lakzaeian, Debra Laefer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper introduces a new method for the automated segmentation of laser scanning data for decorative urban buildings. The method combines octree indexing and RANSAC - two previously established but heretofore not integrated techniques. The approach was successfully applied to terrestrial point clouds of the facades of five highly decorative urban structures for which existing approaches could not provide an automated pipeline. The segmentation technique was relatively efficient and wholly scalable requiring only 1 s per 1,000 points, regardless of the façade’s level of ornamentation or non-recti-linearity. While the technique struggled with shallow protrusions, its ability to process a wide range of building types and opening shapes with data densities as low as 400 pts/m2 demonstrate its inherent potential as part of a large and more sophisticated processing approach.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings
PublisherSpringer Verlag
Pages454-463
Number of pages10
Volume10073 LNCS
ISBN (Print)9783319508313
DOIs
StatePublished - 2016
Event12th International Symposium on Visual Computing, ISVC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10073 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Symposium on Visual Computing, ISVC 2016
CountryUnited States
CityLas Vegas
Period12/12/1612/14/16

Fingerprint

RANSAC
Octree
Facades
Lidar
Segmentation
Pipelines
Scanning
Lasers
Processing
Laser Scanning
Point Cloud
Linearity
Indexing
Range of data
Demonstrate
Buildings

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Hamid-Lakzaeian, F., & Laefer, D. (2016). An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings. In Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings (Vol. 10073 LNCS, pp. 454-463). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10073 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-50832-0_44

An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings. / Hamid-Lakzaeian, Fatemeh; Laefer, Debra.

Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings. Vol. 10073 LNCS Springer Verlag, 2016. p. 454-463 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10073 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hamid-Lakzaeian, F & Laefer, D 2016, An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings. in Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings. vol. 10073 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10073 LNCS, Springer Verlag, pp. 454-463, 12th International Symposium on Visual Computing, ISVC 2016, Las Vegas, United States, 12/12/16. https://doi.org/10.1007/978-3-319-50832-0_44
Hamid-Lakzaeian F, Laefer D. An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings. In Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings. Vol. 10073 LNCS. Springer Verlag. 2016. p. 454-463. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-50832-0_44
Hamid-Lakzaeian, Fatemeh ; Laefer, Debra. / An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings. Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings. Vol. 10073 LNCS Springer Verlag, 2016. pp. 454-463 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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