Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/8423
Author(s): | Gomes, P. Santana, P. Barata, J. |
Date: | 2014 |
Title: | A vision-based approach to fire detection |
Volume: | 11 |
Pages: | 149 |
ISSN: | 1729-8806 |
Keywords: | Vision systems Fire detection Smart cameras Computer vision Object detection Object tracking |
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. |
Peerreviewed: | Sim |
Access type: | Open Access |
Appears in Collections: | CTI-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Files in This Item:
File | Description | Size | Format | |
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IntJAdvRoboticSystems47469.pdf | 2,02 MB | Adobe PDF | View/Open |
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