Swimming pool identification from digital sensor imagery using SVM

David Tien; Tarashankar Rudra; Anthony B. Hope

doi:10.1109/DICTA.2007.4426841

Swimming pool identification from digital sensor imagery using SVM

David Tien^*, Tarashankar Rudra, Anthony B. Hope

^*Corresponding author for this work

Faculty of Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

9 Citations (Scopus)

Abstract

Australia is a country often marred by serious bushfires. In January 2003 it witnessed a significant natural disaster when Canberra was struck by firestorms. The Ash Wednesday fires in Victoria resulted in 75 deaths twenty years earlier. Events like these have made environmental and emergency management research a focus in Australia. In this paper, we introduce a Support Vector Machine (SVM) technique to classify small area water bodies, swimming pools in particular. These features provide a valuable source of water for Emergency Services and play a crucial role in fighting bushfires in urban areas of Australia.

Original language	English
Title of host publication	Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007
Pages	523-527
Number of pages	5
DOIs	https://doi.org/10.1109/DICTA.2007.4426841
Publication status	Published - 2007
Event	Australian Pattern Recognition Society (APRS) - Glenelg, SA, Australia Duration: 3 Dec 2007 → 5 Dec 2007

Other

Other	Australian Pattern Recognition Society (APRS)
Country/Territory	Australia
City	Glenelg, SA
Period	3/12/07 → 5/12/07

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10.1109/DICTA.2007.4426841

Cite this

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title = "Swimming pool identification from digital sensor imagery using SVM",

abstract = "Australia is a country often marred by serious bushfires. In January 2003 it witnessed a significant natural disaster when Canberra was struck by firestorms. The Ash Wednesday fires in Victoria resulted in 75 deaths twenty years earlier. Events like these have made environmental and emergency management research a focus in Australia. In this paper, we introduce a Support Vector Machine (SVM) technique to classify small area water bodies, swimming pools in particular. These features provide a valuable source of water for Emergency Services and play a crucial role in fighting bushfires in urban areas of Australia.",

author = "David Tien and Tarashankar Rudra and Hope, \{Anthony B.\}",

year = "2007",

doi = "10.1109/DICTA.2007.4426841",

language = "English",

isbn = "0769530672",

pages = "523--527",

booktitle = "Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007",

note = "Australian Pattern Recognition Society (APRS) ; Conference date: 03-12-2007 Through 05-12-2007",

}

Tien, D, Rudra, T & Hope, AB 2007, Swimming pool identification from digital sensor imagery using SVM. in Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007., 4426841, pp. 523-527, Australian Pattern Recognition Society (APRS), Glenelg, SA, Australia, 3/12/07. https://doi.org/10.1109/DICTA.2007.4426841

Swimming pool identification from digital sensor imagery using SVM. / Tien, David; Rudra, Tarashankar; Hope, Anthony B.
Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007. 2007. p. 523-527 4426841.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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BT - Proceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007

T2 - Australian Pattern Recognition Society (APRS)

Y2 - 3 December 2007 through 5 December 2007

ER -

Swimming pool identification from digital sensor imagery using SVM

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