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Automatic Detection and Feature Estimation of Windows for Refining Building Facades in 3D Urban Point Clouds : Volume Ii-3, Issue 1 (07/08/2014)

By Aijazi, A.K

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Book Id: WPLBN0004013800
Format Type: PDF Article :
File Size: Pages 8
Reproduction Date: 2015

Title: Automatic Detection and Feature Estimation of Windows for Refining Building Facades in 3D Urban Point Clouds : Volume Ii-3, Issue 1 (07/08/2014)  
Author: Aijazi, A.K
Volume: Vol. II-3, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2014
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Trassoudaine, L., Aijazi, A., & Checchin, P. (2014). Automatic Detection and Feature Estimation of Windows for Refining Building Facades in 3D Urban Point Clouds : Volume Ii-3, Issue 1 (07/08/2014). Retrieved from http://community.worldlibrary.net/


Description
Description: INSTITUT PASCAL, Université Blaise Pascal, Clermont Université, BP 10448, 63000 Clermont-Ferrand, France. This paper presents a method that automatically detects windows of different shapes, in 3D LiDAR point clouds obtained from mobile terrestrial data acquisition systems in the urban environment. The proposed method first segments out 3D points belonging to the building façade from the 3D urban point cloud and then projects them onto a 2D plane parallel to the building façade. After point inversion within a watertight boundary, windows are segmented out based on geometrical information. The window features/parameters are then estimated exploiting both symmetrically corresponding windows in the façade as well as temporally corresponding windows in successive passages, based on analysis of variance measurements. This unique fusion of information not only accommodates for lack of symmetry but also helps complete missing features due to occlusions. The estimated windows are then used to refine the 3D point cloud of the building façade. The results, evaluated on real data using different standard evaluation metrics, demonstrate the efficacy as well as the technical prowess of the method.

Summary
Automatic Detection and Feature Estimation of Windows for Refining Building Facades in 3D Urban Point Clouds

 

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