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http://hdl.handle.net/10071/8423
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Campo DC | Valor | Idioma |
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dc.contributor.author | Gomes, P. | - |
dc.contributor.author | Santana, P. | - |
dc.contributor.author | Barata, J. | - |
dc.date.accessioned | 2015-02-02T18:48:26Z | - |
dc.date.available | 2015-02-02T18:48:26Z | - |
dc.date.issued | 2014 | - |
dc.identifier.issn | 1729-8806 | por |
dc.identifier.uri | https://ciencia.iscte-iul.pt/public/pub/id/18835 | - |
dc.identifier.uri | http://hdl.handle.net/10071/8423 | - |
dc.description | WOS:000341810500001 (Nº de Acesso Web of Science) | - |
dc.description.abstract | This paper presents a vision-based method for fire detection from fixed surveillance smart cameras. The method integrates several well-known techniques properly adapted to cope with the challenges related to the actual deployment of the vision system. Concretely, background subtraction is performed with a context-based learning mechanism so as to attain higher accuracy and robustness. The computational cost of a frequency analysis of potential fire regions is reduced by means of focusing its operation with an attentive mechanism. For fast discrimination between fire regions and fire-coloured moving objects, a new colour-based model of fire’s appearance and a new wavelet-based model of fire’s frequency signature are proposed. To reduce the false alarm rate due to the presence of fire-coloured moving objects, the category and behaviour of each moving object is taken into account in the decision-making. To estimate the expected object’s size in the image plane and to generate geo-referenced alarms, the camera-world mapping is approximated with a GPS-based calibration process. Experimental results demonstrate the ability of the proposed method to detect fires with an average success rate of 93.1 % at a processing rate of 10 Hz, which is often sufficient for real-life applications. | por |
dc.language.iso | eng | por |
dc.publisher | InTech | por |
dc.rights | openAccess | por |
dc.subject | Vision systems | por |
dc.subject | Fire detection | por |
dc.subject | Smart cameras | por |
dc.subject | Computer vision | por |
dc.subject | Object detection | por |
dc.subject | Object tracking | por |
dc.title | A vision-based approach to fire detection | por |
dc.type | article | en_US |
dc.pagination | 149 | por |
dc.publicationstatus | Publicado | por |
dc.peerreviewed | Sim | por |
dc.relation.publisherversion | The definitive version is available at: http://dx.doi.org/10.5772/58821 | por |
dc.journal | International Journal of Advanced Robotic Systems | por |
dc.distribution | Internacional | por |
dc.volume | 11 | por |
degois.publication.firstPage | 149 | por |
degois.publication.title | International Journal of Advanced Robotic Systems | por |
dc.date.updated | 2015-02-02T18:46:15Z | - |
Aparece nas coleções: | CTI-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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IntJAdvRoboticSystems47469.pdf | 2,02 MB | Adobe PDF | Ver/Abrir |
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