Building detection using Bayesian Networks

Stassopoulou, A and Caelli, Terry 2000, Building detection using Bayesian Networks, International Journal of Pattern Recognition and Artificial Intelligence, vol. 14, no. 6, pp. 715-733, doi: 10.1016/S0218-0014(00)00047-7.


Title Building detection using Bayesian Networks
Author(s) Stassopoulou, A
Caelli, TerryORCID iD for Caelli, Terry orcid.org/0000-0001-9281-2556
Journal name International Journal of Pattern Recognition and Artificial Intelligence
Volume number 14
Issue number 6
Start page 715
End page 733
Total pages 19
Publisher WORLD SCIENTIFIC PUBL CO PTE LTD
Publication date 2000-09-01
ISSN 0218-0014
1793-6381
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
building detection
Bayesian networks
probabilistic reasoning
corner detection
machine learning
adaptive multiscale segmentation
IMAGE INTERPRETATION
TEXTURED IMAGES
BELIEF NETWORKS
SEGMENTATION
SYSTEM
Summary This paper further explores the uses of Bayesian Networks for detecting buildings from digital orthophotos. This work differs from current research in building detection in so far as it utilizes the ability of Bayesian Networks to provide probabilistic methods for evidence combination and, via training, to determine how such evidence should be weighted to maximize classification. In this vein, then, we have also utilized expert performance to not only configure the network values but also to adapt the feature extraction pre-processing units to fit human behavior as closely as possible. Results from digital orthophotos of the Washington DC area prove that such an approach is feasible, robust and worth further analysis.
Language eng
DOI 10.1016/S0218-0014(00)00047-7
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
1702 Cognitive Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30138473

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