Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

article · ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · 2012

AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE

Eunju Kwak, M. Al-Durgham, Ayman Habib

Cited by 21Open access

Abstract

Abstract. Digital Building Model is an important component in many applications such as city modelling, natural disaster planning, and aftermath evaluation. The importance of accurate and up-to-date building models has been discussed by many researchers, and many different approaches for efficient building model generation have been proposed. They can be categorised according to the data source used, the data processing strategy, and the amount of human interaction. In terms of data source, due to the limitations of using single source data, integration of multi-senor data is desired since it preserves the advantages of the involved datasets. Aerial imagery and LiDAR data are among the commonly combined sources to obtain 3D building models with good vertical accuracy from laser scanning and good planimetric accuracy from aerial images. The most used data processing strategies are data-driven and model-driven ones. Theoretically one can model any shape of buildings using data-driven approaches but practically it leaves the question of how to impose constraints and set the rules during the generation process. Due to the complexity of the implementation of the data-driven approaches, model-based approaches draw the attention of the researchers. However, the major drawback of model-based approaches is that the establishment of representative models involves a manual process that requires human intervention. Therefore, the objective of this research work is to automatically generate building models using the Minimum Bounding Rectangle algorithm and sequentially adjusting them to combine the advantages of image and LiDAR datasets.

Cite this paper

APA 7

Kwak, E., Al-Durgham, M., & Habib, A. (2012). AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences, XXXIX-B3, 285–290. https://doi.org/10.5194/isprsarchives-xxxix-b3-285-2012

MLA 9

Kwak, Eunju, et al. “AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE.” ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences, vol. XXXIX-B3, 2012, pp. 285–90, https://doi.org/10.5194/isprsarchives-xxxix-b3-285-2012.

Chicago

Kwak, Eunju, M. Al-Durgham, and Ayman Habib. 2012. “AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE.” ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences XXXIX-B3: 285–90. https://doi.org/10.5194/isprsarchives-xxxix-b3-285-2012.

Harvard

Kwak, E., Al-Durgham, M. and Habib, A. (2012) ‘AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE’, ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences, XXXIX-B3, pp. 285–290. Available at: https://doi.org/10.5194/isprsarchives-xxxix-b3-285-2012.

BibTeX
@article{kwak2012automatic,
  title = {{AUTOMATIC 3D BUILDING MODEL GENERATION FROM LIDAR AND IMAGE DATA USING SEQUENTIAL MINIMUM BOUNDING RECTANGLE}},
  author = {Kwak, Eunju and Al-Durgham, M. and Habib, Ayman},
  journal = {˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences},
  volume = {XXXIX-B3},
  pages = {285--290},
  year = {2012},
  doi = {10.5194/isprsarchives-xxxix-b3-285-2012}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers