Video fire detection - Review
dc.authorid | Dimitropoulos, Kosmas/0000-0003-1584-7047 | |
dc.authorid | Toreyin, Behcet Ugur/0000-0003-4406-2783 | |
dc.authorid | Grammalidis, Nikos/0000-0001-8465-6258 | |
dc.authorscopusid | 57197548971 | |
dc.authorscopusid | 22950021000 | |
dc.authorscopusid | 6504518697 | |
dc.authorscopusid | 6701851845 | |
dc.authorscopusid | 36052828800 | |
dc.authorscopusid | 49061188200 | |
dc.authorscopusid | 9249500700 | |
dc.authorwosid | Grammalidis, Nikos/U-9411-2019 | |
dc.authorwosid | Toreyin, Behcet Ugur/A-6780-2012 | |
dc.contributor.author | Cetin, A. Enis | |
dc.contributor.author | Töreyin, Behçet Uğur | |
dc.contributor.author | Dimitropoulos, Kosmas | |
dc.contributor.author | Gouverneur, Benedict | |
dc.contributor.author | Grammalidis, Nikos | |
dc.contributor.author | Gunay, Osman | |
dc.contributor.author | Habiboglu, Y. Hakan | |
dc.contributor.author | Verstockt, Steven | |
dc.contributor.authorID | 19325 | tr_TR |
dc.contributor.authorID | 2147 | tr_TR |
dc.contributor.other | Elektrik-Elektronik Mühendisliği | |
dc.date.accessioned | 2017-03-03T13:36:11Z | |
dc.date.available | 2017-03-03T13:36:11Z | |
dc.date.issued | 2013 | |
dc.department | Çankaya University | en_US |
dc.department-temp | [Cetin, A. Enis; Gunay, Osman; Habiboglu, Y. Hakan] Bilkent Univ, Dept Elect & Elect Engn, TR-06533 Ankara, Turkey; [Dimitropoulos, Kosmas; Grammalidis, Nikos] Ctr Res & Technol Hellas, Inst Informat Technol, Thermi 57001, Greece; [Gouverneur, Benedict] Xen Infrared Solut, Louvain, Belgium; [Toreyin, B. Ugur] Cankaya Univ, Dept Elect & Commun Engn, Ankara, Turkey; [Verstockt, Steven] Univ Ghent, iMinds, ELIS Dept, Multimedia Lab, Ledeberg Ghent, Belgium | en_US |
dc.description | Dimitropoulos, Kosmas/0000-0003-1584-7047; Toreyin, Behcet Ugur/0000-0003-4406-2783; Grammalidis, Nikos/0000-0001-8465-6258 | en_US |
dc.description.abstract | This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor "volumes" and do not have transport delay that the traditional "point" sensors suffer from. It is possible to cover an area of 100 km(2) using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation. (c) 2013 Elsevier Inc. All rights reserved. | en_US |
dc.description.publishedMonth | 12 | |
dc.description.sponsorship | FIRESENSE (Fire Detection and Management through a Multi-Sensor Network for the Protection of Cultural Heritage Areas from the Risk of Fire and Extreme Weather Conditions) [FP7-ENV-2009-1244088-FIRESENSE]; Scientific and Technological Research Council of Turkey (TUBITAK) [EEEAG 111E217] | en_US |
dc.description.sponsorship | This work was supported in part by FIRESENSE (Fire Detection and Management through a Multi-Sensor Network for the Protection of Cultural Heritage Areas from the Risk of Fire and Extreme Weather Conditions, FP7-ENV-2009-1244088-FIRESENSE) and by The Scientific and Technological Research Council of Turkey (TUBITAK) under grant EEEAG 111E217. | en_US |
dc.description.woscitationindex | Science Citation Index Expanded | |
dc.identifier.citation | Çetin, A.E...et al. (2013). Video fire detection - Review. Digital Signal Processing, 23(6), 1827-1843. http://dx.doi.org/10.1016/j.dsp.2013.07.003 | en_US |
dc.identifier.doi | 10.1016/j.dsp.2013.07.003 | |
dc.identifier.endpage | 1843 | en_US |
dc.identifier.issn | 1051-2004 | |
dc.identifier.issn | 1095-4333 | |
dc.identifier.issue | 6 | en_US |
dc.identifier.scopus | 2-s2.0-84884910172 | |
dc.identifier.scopusquality | Q2 | |
dc.identifier.startpage | 1827 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.dsp.2013.07.003 | |
dc.identifier.volume | 23 | en_US |
dc.identifier.wos | WOS:000325383800001 | |
dc.identifier.wosquality | Q2 | |
dc.language.iso | en | en_US |
dc.publisher | Academic Press inc Elsevier Science | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.scopus.citedbyCount | 267 | |
dc.subject | Video Based Fire Detection | en_US |
dc.subject | Computer Vision | en_US |
dc.subject | Smoke Detection | en_US |
dc.subject | Wavelets | en_US |
dc.subject | Covariance Matrices | en_US |
dc.subject | Decision Fusion | en_US |
dc.title | Video fire detection - Review | tr_TR |
dc.title | Video Fire Detection - Review | en_US |
dc.type | Article | en_US |
dc.wos.citedbyCount | 204 | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 31d067df-3d94-4058-a635-943b70f82ea4 | |
relation.isAuthorOfPublication.latestForDiscovery | 31d067df-3d94-4058-a635-943b70f82ea4 | |
relation.isOrgUnitOfPublication | a8b0a996-7c01-41a1-85be-843ba585ef45 | |
relation.isOrgUnitOfPublication.latestForDiscovery | a8b0a996-7c01-41a1-85be-843ba585ef45 |
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