Fusion of lidar data and optical imagery for building modeling

Liang Chien Chen, Tee Ann Teo, Yi Chen Shao, Yen Chung Lai, Jiann-Yeou Rau

研究成果: Conference article

64 引文 (Scopus)

摘要

This paper presents a scheme for building detection and building reconstruction from LIDAR data and optical imagery. The proposed scheme comprises two major parts: (1) detection of building regions, and (2) reconstruction of building models. Spatial registration of LIDAR data and optical images is performed as data preprocessing. Then, at the first stage, a region-based segmentation and knowledge-based classification are integrated to detect building regions. Once the building regions are detected, we analyze the coplanarity of the LIDAR raw data to shape the roof. The accurate position of walls of the building is determined by the integration of the edges extracted from optical imagery. Thus the three dimensional building edges can be used for the reconstruction. A patented method SMS (Split-Merge-Shape) is employed to generated building models in the last step. Having the advantages of high reliability and flexibility, the SMS method provides stable reconstruction even when those 3D building lines are broken. LIDAR data acquired by Leica ALS 40, QuickBird multispectral satellite images and aerial images were used in the validation.

原文English
期刊International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
35
出版狀態Published - 2004 一月 1
事件20th ISPRS Congress on Technical Commission VII - Istanbul, Turkey
持續時間: 2004 七月 122004 七月 23

指紋

Optical radar
lidar
imagery
Fusion reactions
reconstruction
Roofs
modeling
Satellites
Antennas
QuickBird
segmentation
roof
flexibility
knowledge
detection
method

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

引用此文

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AU - Teo, Tee Ann

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AU - Rau, Jiann-Yeou

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N2 - This paper presents a scheme for building detection and building reconstruction from LIDAR data and optical imagery. The proposed scheme comprises two major parts: (1) detection of building regions, and (2) reconstruction of building models. Spatial registration of LIDAR data and optical images is performed as data preprocessing. Then, at the first stage, a region-based segmentation and knowledge-based classification are integrated to detect building regions. Once the building regions are detected, we analyze the coplanarity of the LIDAR raw data to shape the roof. The accurate position of walls of the building is determined by the integration of the edges extracted from optical imagery. Thus the three dimensional building edges can be used for the reconstruction. A patented method SMS (Split-Merge-Shape) is employed to generated building models in the last step. Having the advantages of high reliability and flexibility, the SMS method provides stable reconstruction even when those 3D building lines are broken. LIDAR data acquired by Leica ALS 40, QuickBird multispectral satellite images and aerial images were used in the validation.

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