| International Journal of Advanced Robotic Systems | |
| A Vision-Based Approach to Fire Detection: | |
| PedroGomes1  | |
| 关键词: Vision Systems; Fire Detection; Smart Cameras; Computer Vision; Object Detection & Tracking; | |
| DOI : 10.5772/58821 | |
| 学科分类:自动化工程 | |
| 来源: InTech | |
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【 摘 要 】
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.
【 授权许可】
CC BY
【 预 览 】
| Files | Size | Format | View |
|---|---|---|---|
| RO201901231143784ZK.pdf | 1991KB |
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