Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery

Liang Chien Chen, Tee Ann Teo, Chi Heng Hsieh, Jiann-Yeou Rau

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

29 Citations (Scopus)

Abstract

This paper presents a scheme to detect building regions, followed by a reconstruction procedure. Airborne LIDAR data and aerial imagery are integrated in the proposed scheme. In light of the different buildings, we target the ones with straight and curvilinear boundaries. In the detection stage, a region-based segmentation and object-based classification are integrated. In the building reconstruction, we perform an edge detection to obtain the initial building lines from the rasterized LIDAR data. The accurate arcs and straight lines are then obtained in the image space. By employing the roof analysis, we determine the three dimensional building structure lines. Finally, the Split-Merge-Shape method is applied to generate the building models. Experimental results indicate that the success rate of the building detection reaches 91%. Among the successfully detected buildings, 90% of the buildings are fully or partially reconstructed. The planimetric accuracy of the building boundaries is better than 0.8m, while the shaping error of reconstructed roofs in height is 0.14 m.

Original languageEnglish
Title of host publicationAdvances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings
Pages24-33
Number of pages10
DOIs
Publication statusPublished - 2006 Dec 1
Event1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006 - Hsinchu, Taiwan
Duration: 2006 Dec 102006 Dec 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4319 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006
CountryTaiwan
CityHsinchu
Period06-12-1006-12-13

Fingerprint

Laser Scanner
Antennas
Lasers
Roofs
Image Space
Line
Edge Detection
Straight Line
Straight
Arc of a curve
Edge detection
Segmentation
Three-dimensional
Target
Experimental Results
Buildings
Imagery

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Chen, L. C., Teo, T. A., Hsieh, C. H., & Rau, J-Y. (2006). Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery. In Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings (pp. 24-33). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4319 LNCS). https://doi.org/10.1007/11949534-3
Chen, Liang Chien ; Teo, Tee Ann ; Hsieh, Chi Heng ; Rau, Jiann-Yeou. / Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery. Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. 2006. pp. 24-33 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{8d9f1aea09514b368dd24abffcfb45f2,
title = "Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery",
abstract = "This paper presents a scheme to detect building regions, followed by a reconstruction procedure. Airborne LIDAR data and aerial imagery are integrated in the proposed scheme. In light of the different buildings, we target the ones with straight and curvilinear boundaries. In the detection stage, a region-based segmentation and object-based classification are integrated. In the building reconstruction, we perform an edge detection to obtain the initial building lines from the rasterized LIDAR data. The accurate arcs and straight lines are then obtained in the image space. By employing the roof analysis, we determine the three dimensional building structure lines. Finally, the Split-Merge-Shape method is applied to generate the building models. Experimental results indicate that the success rate of the building detection reaches 91{\%}. Among the successfully detected buildings, 90{\%} of the buildings are fully or partially reconstructed. The planimetric accuracy of the building boundaries is better than 0.8m, while the shaping error of reconstructed roofs in height is 0.14 m.",
author = "Chen, {Liang Chien} and Teo, {Tee Ann} and Hsieh, {Chi Heng} and Jiann-Yeou Rau",
year = "2006",
month = "12",
day = "1",
doi = "10.1007/11949534-3",
language = "English",
isbn = "354068297X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "24--33",
booktitle = "Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings",

}

Chen, LC, Teo, TA, Hsieh, CH & Rau, J-Y 2006, Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery. in Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4319 LNCS, pp. 24-33, 1st Pacific Rim Symposium on Image and Video Technology, PSIVT 2006, Hsinchu, Taiwan, 06-12-10. https://doi.org/10.1007/11949534-3

Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery. / Chen, Liang Chien; Teo, Tee Ann; Hsieh, Chi Heng; Rau, Jiann-Yeou.

Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. 2006. p. 24-33 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4319 LNCS).

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

TY - GEN

T1 - Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery

AU - Chen, Liang Chien

AU - Teo, Tee Ann

AU - Hsieh, Chi Heng

AU - Rau, Jiann-Yeou

PY - 2006/12/1

Y1 - 2006/12/1

N2 - This paper presents a scheme to detect building regions, followed by a reconstruction procedure. Airborne LIDAR data and aerial imagery are integrated in the proposed scheme. In light of the different buildings, we target the ones with straight and curvilinear boundaries. In the detection stage, a region-based segmentation and object-based classification are integrated. In the building reconstruction, we perform an edge detection to obtain the initial building lines from the rasterized LIDAR data. The accurate arcs and straight lines are then obtained in the image space. By employing the roof analysis, we determine the three dimensional building structure lines. Finally, the Split-Merge-Shape method is applied to generate the building models. Experimental results indicate that the success rate of the building detection reaches 91%. Among the successfully detected buildings, 90% of the buildings are fully or partially reconstructed. The planimetric accuracy of the building boundaries is better than 0.8m, while the shaping error of reconstructed roofs in height is 0.14 m.

AB - This paper presents a scheme to detect building regions, followed by a reconstruction procedure. Airborne LIDAR data and aerial imagery are integrated in the proposed scheme. In light of the different buildings, we target the ones with straight and curvilinear boundaries. In the detection stage, a region-based segmentation and object-based classification are integrated. In the building reconstruction, we perform an edge detection to obtain the initial building lines from the rasterized LIDAR data. The accurate arcs and straight lines are then obtained in the image space. By employing the roof analysis, we determine the three dimensional building structure lines. Finally, the Split-Merge-Shape method is applied to generate the building models. Experimental results indicate that the success rate of the building detection reaches 91%. Among the successfully detected buildings, 90% of the buildings are fully or partially reconstructed. The planimetric accuracy of the building boundaries is better than 0.8m, while the shaping error of reconstructed roofs in height is 0.14 m.

UR - http://www.scopus.com/inward/record.url?scp=70350292685&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70350292685&partnerID=8YFLogxK

U2 - 10.1007/11949534-3

DO - 10.1007/11949534-3

M3 - Conference contribution

SN - 354068297X

SN - 9783540682974

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 24

EP - 33

BT - Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings

ER -

Chen LC, Teo TA, Hsieh CH, Rau J-Y. Reconstruction of building models with curvilinear boundaries from laser scanner and aerial imagery. In Advances in Image and Video Technology - First Pacific Rim Symposium, PSIVT 2006, Proceedings. 2006. p. 24-33. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11949534-3