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dc.contributor.authorVerstockt, S.en_US
dc.contributor.authorHoecke, S. V.en_US
dc.contributor.authorBeji, T.en_US
dc.contributor.authorMerci, B.en_US
dc.contributor.authorGouverneur, B.en_US
dc.contributor.authorCetin, A. E.en_US
dc.contributor.authorPotter, P. D.en_US
dc.contributor.authorWalle, R. V. D.en_US
dc.date.accessioned2016-02-08T09:41:46Z
dc.date.available2016-02-08T09:41:46Z
dc.date.issued2013en_US
dc.identifier.issn0379-7112
dc.identifier.urihttp://hdl.handle.net/11693/21139
dc.description.abstractIn this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by visual flame feature analysis and amplitude disorder detection. In order to detect the low-cost flame related features, moving objects in visual images are analyzed over time. If an object possesses high probability for each of the flame characteristics, it is labeled as candidate flame region. Simultaneously, the amplitude disorder is also investigated. Also labeled as candidate flame regions are regions with high accumulative amplitude differences and high values in all detail images of the amplitude image's discrete wavelet transform. Finally, when there is overlap of at least one of the visual and amplitude candidate flame regions, fire alarm is raised. The smoke detector, on the other hand, focuses on global changes in the depth images of the time-of-flight camera, which do not have significant impact on the amplitude images. It was found that this behavior is unique for smoke. Experiments show that the proposed detectors improve the accuracy of fire detection in car parks. The flame detector has an average flame detection rate of 93%, with hardly any false positive detection, and the smoke detection rate of the TOF based smoke detector is 88%.en_US
dc.language.isoEnglishen_US
dc.source.titleFire Safety Journalen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.firesaf.2012.07.005en_US
dc.subjectFlame detectionen_US
dc.subjectMulti-modal video analysisen_US
dc.subjectSmoke detectionen_US
dc.subjectTime-of-flight imagingen_US
dc.subjectVideo fire detectionen_US
dc.subjectVideo surveillanceen_US
dc.subjectFire detectionen_US
dc.subjectFlame detectionen_US
dc.subjectSmoke detectionen_US
dc.subjectTime-of-flight imagingen_US
dc.subjectVideo analysisen_US
dc.subjectVideo surveillanceen_US
dc.subjectAmplitude modulationen_US
dc.subjectCamerasen_US
dc.subjectDiscrete wavelet transformsen_US
dc.subjectGarages (parking)en_US
dc.subjectParkingen_US
dc.subjectSecurity systemsen_US
dc.subjectSmoke detectorsen_US
dc.subjectDetectorsen_US
dc.titleA multi-modal video analysis approach for car park fire detectionen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage44en_US
dc.citation.epage57en_US
dc.citation.volumeNumber57en_US
dc.identifier.doi10.1016/j.firesaf.2012.07.005en_US
dc.publisherElsevieren_US


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