Performance evaluation and analysis of monocular buildingextraction from aerial imagery
Shufelt, J.A.
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Apr 1999
Volume: 21,
Issue: 4
On page(s): 311-326
ISSN: 0162-8828
References Cited: 43
CODEN: ITPIDJ
INSPEC Accession Number: 6242783
Digital Object Identifier: 10.1109/34.761262
Current Version Published: 2002-08-06
Abstract
Research in monocular building extraction from aerial imagery has
neglected performance evaluation in three areas: unbiased metrics for
quantifying detection and delineation performance, an evaluation
methodology for applying these metrics to a representative body of test
imagery, and an approach for understanding the impact of image and scene
content on building extraction algorithms. This paper addresses these
areas with an end-to-end performance evaluation of four existing
monocular building extraction systems, using image space and object
space-based metrics on 83 test images of 18 sites. This analysis is
supplemented by an examination of the effects of image obliquity and
object complexity on system performance, as well as a case study on the
effects of edge fragmentation. This widely applicable performance
evaluation approach highlights the consequences of various traditional
assumptions about camera geometry, image content and scene structure,
and demonstrates the utility of rigorous photogrammetric object space
modeling and primitive-based representations for building extraction
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