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Video-based fire detection with spatio-temporal SURF and color features

机译:基于视频的火灾探测,具有时空SURF和色彩特征

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This paper proposes a new video-based method for fire detection, which uses color, spatial and temporal information. Our method divides videos into spatio-temporal blocks and extracts a novel volume SURF features from three orthogonal planes of these blocks. Combining spatio-temporal SURF features and the global color histogram of Lab color space on blocks, we achieve a new final features to detect fire. And we use a linear SVM in classification stage. Experiments show that the classification performance of our proposed method is better than a previous method and can achieve better true positive rate in various scenes.
机译:本文提出了一种基于视频的火灾探测新方法,该方法利用颜色,空间和时间信息。我们的方法将视频划分为时空块,并从这些块的三个正交平面提取新的体SURF特征。结合时空SURF特征和块上Lab颜色空间的全局颜色直方图,我们获得了一种新的最终特征来检测火灾。并且我们在分类阶段使用线性支持向量机。实验表明,本文提出的方法的分类性能优于以前的方法,并能在各种场景下获得更好的真实阳性率。

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