Applying Fuzzy Logic in Video Surveillance Systems

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dc.contributor.author Molina, JM
dc.contributor.author Garcia, J
dc.contributor.author Concha, OP
dc.contributor.author Carbo, J
dc.contributor.author Berlanga, A
dc.contributor.author Portillo, J
dc.date.accessioned 2012-02-02T09:58:18Z
dc.date.issued 2005-01
dc.identifier.citation Mathware and Soft Computing, 2005, 12 (3), pp. 185 - 198
dc.identifier.issn 1134-5632
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/15177
dc.description.abstract In this work, the application of fuzzy logic in surveillance systems based on cameras is analyzed. Three different fuzzy systems have been tested and compared with a crisp decision system. The first one has been developed using an expert knowledge, the second one was learned from recorded videos, and a third one is developed as a refinement taking into account evaluation with ground truth. In all cases, the core of the system is the association function, in which the developed fuzzy system takes decision about what blobs (detected pixels grouped in a zone) belong to what tracks. In this work the surveillance video system is deployed in an airport. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The system evaluation has been developed using an evaluation function specifically designed for this type of problem. Results obtained with real data in representative ground operations show different capabilities for each system to solve complex scenarios and to improve tracking accuracy.
dc.format Scott McWhirter
dc.publisher Universidad de Granada
dc.title Applying Fuzzy Logic in Video Surveillance Systems
dc.type Journal Article
dc.parent Mathware and Soft Computing
dc.journal.volume 3
dc.journal.volume 12
dc.journal.number 3 en_US
dc.publocation Spain en_US
dc.identifier.startpage 185 en_US
dc.identifier.endpage 198 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 104828
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


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