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Model-based automatic building extra...

Seo, Suyoung.

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Model-based automatic building extraction from lidar and aerial imagery.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model-based automatic building extraction from lidar and aerial imagery./
Author:	Seo, Suyoung.
Description:	139 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2561.
Contained By:	Dissertation Abstracts International64-06B.
Subject:	Geodesy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3093696

Model-based automatic building extraction from lidar and aerial imagery.
Seo, Suyoung.

Model-based automatic building extraction from lidar and aerial imagery. - 139 p.

Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2561.

Thesis (Ph.D.)--The Ohio State University, 2003.

The automatic recognition and reconstruction of buildings from sensory input data is an important research topic with widespread applications in city modeling, urban planning, environmental studies, and telecommunication. This study presents integration methods to increase the level of automation in building recognition and reconstruction. Aerial imagery has been used as a major source in mapping fields and, in recent years, LIDAR data became popular as another type of mapping resource. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. LIDAR data provide direct information about heights of object surfaces but have limitations with respect to boundary localization. Efficient methods to generate building boundary hypotheses and localize object features are described. Such methods use complementary characteristics of two sensors. Graph data structures are used for interpreting surface discontinuities. Buildings are recognized by analyzing contour 1 graphs and modeled with surface patches from LIDAR data. Building model hypotheses are generated as a combination of wing models and are verified by assessing the consistency between corresponding data sets. Experiments using aerial imagery and LIDAR data are presented. Three findings are noted: First, building boundaries are successfully recognized using the proposed contour analysis method. Second, the wing model and hypothesized contours increase the level of automation in building hypothesis generation/verification. Third, the integration of aerial images and LIDAR data enhances the accuracy of reconstructed buildings in the horizontal and vertical directions.Subjects--Topical Terms:

550741
Geodesy.

Model-based automatic building extraction from lidar and aerial imagery.
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035 $a (UnM)AAI3093696
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040 $a UnM $c UnM
100 1 $a Seo, Suyoung. $3 1952330
245 1 0 $a Model-based automatic building extraction from lidar and aerial imagery.
300 $a 139 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2561.
500 $a Adviser: Anton F. Schenk.
502 $a Thesis (Ph.D.)--The Ohio State University, 2003.
520 $a The automatic recognition and reconstruction of buildings from sensory input data is an important research topic with widespread applications in city modeling, urban planning, environmental studies, and telecommunication. This study presents integration methods to increase the level of automation in building recognition and reconstruction. Aerial imagery has been used as a major source in mapping fields and, in recent years, LIDAR data became popular as another type of mapping resource. Regarding their performances, aerial imagery has the ability to delineate object boundaries but omits much of these boundaries during feature extraction. LIDAR data provide direct information about heights of object surfaces but have limitations with respect to boundary localization. Efficient methods to generate building boundary hypotheses and localize object features are described. Such methods use complementary characteristics of two sensors. Graph data structures are used for interpreting surface discontinuities. Buildings are recognized by analyzing contour 1 graphs and modeled with surface patches from LIDAR data. Building model hypotheses are generated as a combination of wing models and are verified by assessing the consistency between corresponding data sets. Experiments using aerial imagery and LIDAR data are presented. Three findings are noted: First, building boundaries are successfully recognized using the proposed contour analysis method. Second, the wing model and hypothesized contours increase the level of automation in building hypothesis generation/verification. Third, the integration of aerial images and LIDAR data enhances the accuracy of reconstructed buildings in the horizontal and vertical directions.
590 $a School code: 0168.
650 4 $a Geodesy. $3 550741
650 4 $a Engineering, Civil. $3 783781
690 $a 0370
690 $a 0543
710 2 0 $a The Ohio State University. $3 718944
773 0 $t Dissertation Abstracts International $g 64-06B.
790 1 0 $a Schenk, Anton F., $e advisor
790 $a 0168
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3093696