TY - GEN
T1 - An integrated octree-RANSAC technique for automated LiDAR building data segmentation for decorative buildings
AU - Hamid-Lakzaeian, Fatemeh
AU - Laefer, Debra F.
N1 - Funding Information:
This work was generously funded by the European Research Council grant ERC-2012-StG-20111012 ‘RETURN-Rethinking Tunnelling in Urban Neighbourhoods’ Project 307836. The authors gratefully thank Donal Lennon for the pre-processing of the data sets, as well as for assistance with data acquisition.
Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-319-50832-0_44
DO - 10.1007/978-3-319-50832-0_44
M3 - Conference contribution
AN - SCOPUS:85007291951
SN - 9783319508313
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 454
EP - 463
BT - Advances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings
A2 - Bebis, George
A2 - Koracin, Darko
A2 - Isenberg, Tobias
A2 - Skaff, Sandra
A2 - Sadagic, Amela
A2 - Boyle, Richard
A2 - Porikli, Fatih
A2 - Min, Jianyuan
A2 - Scheidegger, Carlos
A2 - Entezari, Alireza
A2 - Parvin, Bahram
A2 - Iwai, Daisuke
PB - Springer Verlag
T2 - 12th International Symposium on Visual Computing, ISVC 2016
Y2 - 12 December 2016 through 14 December 2016
ER -