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	Smoke detection based on a semi-supervised clustering model
	He, Haiqian ; Peng, Liqun ; Yang, Deshun ; Chen, Xiaoou
	2014
英文摘要	Video-based smoke detection is regarded as an effective way for fire detection in open spaces. In this paper, a classification model based on a semi-supervised clustering method is introduced to improve the performance of smoke detection. In our model, we present a novel method to automatically determine the number of clusters K. Considering the randomness of the initial centers in K-means++, a voting strategy is proposed to maintain a stable clustering performance. Besides, the scene-related information is added to our clustering data to obtain a self-adaptive model. Finally, the experimental results show that our classification model outperforms other state-of-the-art methods and has great improvement in terms of generalization (i.e. can adapt to the unknown scenes). ? 2014 Springer International Publishing.; EI; 0
语种	英语
DOI标识	10.1007/978-3-319-04117-9_27
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/321426]
专题	计算机科学技术研究所
推荐引用方式 GB/T 7714	He, Haiqian,Peng, Liqun,Yang, Deshun,et al. Smoke detection based on a semi-supervised clustering model. 2014-01-01.

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