World Library  

QR link for Automatic 3D Building Model Generation from Lidar and Image Data Using Sequential Minimum Bounding Rectangle : Volume Xxxix-b3, Issue 1 (31/07/2012)
Add to Book Shelf
Flag as Inappropriate
Email this Book

Automatic 3D Building Model Generation from Lidar and Image Data Using Sequential Minimum Bounding Rectangle : Volume Xxxix-b3, Issue 1 (31/07/2012)

By Kwak, E.

Click here to view

Book Id: WPLBN0004016508
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Automatic 3D Building Model Generation from Lidar and Image Data Using Sequential Minimum Bounding Rectangle : Volume Xxxix-b3, Issue 1 (31/07/2012)  
Author: Kwak, E.
Volume: Vol. XXXIX-B3, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus Publications
Historic
Publication Date:
2012
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Al-Durgham, M., Habib, A., & Kwak, E. (2012). Automatic 3D Building Model Generation from Lidar and Image Data Using Sequential Minimum Bounding Rectangle : Volume Xxxix-b3, Issue 1 (31/07/2012). Retrieved from http://community.worldlibrary.net/


Description
Description: Dept. of Geomatics Engineering, University of Calgary, 2500 University Drive, Calgary, T2N 1N4, AB, Canada. 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.

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

 

Click To View

Additional Books


  • Feature Evaluation for Building Facade I... (by )
  • High Resolution Airborne Shallow Water M... (by )
  • The Potential of Geomatics in the Realiz... (by )
  • Research on Estimation Crop Planting Are... (by )
  • The Isprs Student Consortium: from Launc... (by )
  • Real Time Speed Estimation from Monocula... (by )
  • Land Use and Land Cover Classification f... (by )
  • Spectral Mixture Analysis (Sma) of Lands... (by )
  • Primitive-based 3D Building Reconstructi... (by )
  • Extraction of Aqueous Minerals on Mars U... (by )
  • Conservation and Valorization of the His... (by )
  • Endmember Extraction for Hyperspectral I... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.