Real-time wildfire detection using correlation descriptors
Real-time wildfire detection using correlation descriptors
复制标题
使用相关描述符进行实时野火检测
DOI：
10.5281/zenodo.42544
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
A. Cetin
中科院分区：
文献类型：
--
作者：
Y. H. Habiboglu;Osman Günay;A. Cetin
提出了一种基于时空相关描述符的视频野火探测系统。在野火的最初阶段，在火焰之前可以看到烟羽。该方法利用背景减法和颜色阈值来寻找视频中烟雾色的慢动区域。将这些区域划分为多个时空块，并从中提取相关特征。表示烟雾区域的空间和时间特征的属性集用于形成相关描述符。使用包含烟雾和烟雾颜色物体的视频数据中获得的描述符对SVM分类器进行训练和测试。给出了实验结果。
A video based wildfire detection system that based on spatio-temporal correlation descriptors is developed. During the initial stages of wildfires smoke plume becomes visible before the flames. The proposed method uses background subtraction and color thresholds to find the smoke colored slow moving regions in video. These regions are divided into spatio-temporal blocks and correlation features are extracted from the blocks. Property sets that represent both the spatial and the temporal characteristics of smoke regions are used to form correlation descriptors. An SVM classifier is trained and tested with descriptors obtained from video data containing smoke and smoke colored objects. Experimental results are presented.