电子科技大学学报2016，Vol.46Issue(6)：992-996,5.DOI:10.3969/j.issn.1001-0548.2016.06.020
基于级联卷积神经网络的视频动态烟雾检测
Dynamic Smoke Detection Using Cascaded Convolutional Neural Network for Surveillance Videos
摘要
Abstract
The extraction of stable smoke features in complex scenes is a challenging task for video based smoke detection. For this issue, a convolutional neural network (CNN) framework which employs both static and dynamic features of the smoke is proposed. On the basis of analyzing the static features of individual frame, we further explore the dynamic features in spatial-temporal domain to reduce the influence of the noise from environment. Experimental results show that the proposed cascaded convolutional neural network framework performs well in real-time video based smoke detection for complex scenes.关键词
卷积神经网络/深度学习/纹理特征/视频烟雾检测Key words
convolutional neural networks/deep learning/texture features/video smoke detection分类
信息技术与安全科学引用本文复制引用
陈俊周,汪子杰,陈洪瀚,左林翼..基于级联卷积神经网络的视频动态烟雾检测[J].电子科技大学学报,2016,46(6):992-996,5.基金项目
国家自然科学基金(61003143,61202191) （61003143,61202191）
