DocumentCode :
711742
Title :
Assessing validation methods for building identification and extraction
Author :
Wentz, Elizabeth A. ; Qunshan Zhao
Author_Institution :
Sch. of Geogr. Sci. & Urban Planning, Arizona State Univ., Tempe, AZ, USA
fYear :
2015
fDate :
March 30 2015-April 1 2015
Firstpage :
1
Lastpage :
4
Abstract :
As data sources and algorithm choices become increasingly more available for automatically extracting and reconstructing 3D buildings, methods are needed to assess the accuracy of the classification process. Our research goal is to compare validation data sources and methods to assess objectivity, sensitivity, and reliability of current validation approaches. Our results show that when relying on object-oriented methods for building classification and extraction, methods other than pixel assessment are needed.
Keywords :
buildings (structures); feature extraction; geophysical image processing; image classification; image reconstruction; object-oriented methods; remote sensing; 3D building reconstruction; assessing validation method; building classification; building extraction; building identification; classification process accuracy assessment; data source; object-oriented method; objectivity assessment; reliability assessment; sensitivity assessment; Accuracy; Buildings; Data mining; Image reconstruction; Laser radar; Remote sensing; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Urban Remote Sensing Event (JURSE), 2015 Joint
Conference_Location :
Lausanne
Type :
conf
DOI :
10.1109/JURSE.2015.7120453
Filename :
7120453
Link To Document :
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