摘要
视频火焰检测是计算机视觉中一项理论意义与实际价值兼备的重要课题,对烟火事故的消防安全具有重要的实际意义。随着火焰视觉特征模型的不断完善,视频火焰检测方法的研究得到发展。本文综述了视频火焰检测的几个主要方面,包括其相对传统检测器的优势、火焰特性的分类与描述、代表性的检测方法、典型的系统方案及其发展趋势等;探讨了其中涉及的系统通用性、实时性、智能性、评测标准和多传感器融合等关键问题;还介绍了一种新的基于层次注意的视频火焰检测模型及多源感知信息的显著性融合框架,尝试借助显著性特征描述和低冗余计算来提升烟火监测系统的效率和主动性。
Video Fire Detection （VFD） is one of the most active research topics being valuable for both theoretical and practical research in computer vision, especially has a wide spectrum of promising applications in video surveillance for early fire alarms in public security. As the improvement on visual feature model of fire, many VFD systems have been developed. In this paper, some main issues on VFD are reviewed, including its advantages to traditional detectors, the classification and description for visual fire features, the representative algorithms and systems, the future trends, and so on. Then some key problems on the compatibility, real-time efficiency, intelligence, performance evaluation and multi sensor fusion for VFD are discussed. In addition, a novel VFD model based on hierarchical attention and a saliency fusion framework based on multi sensors are proposed for boosting the efficiency and activity of fire surveillance by using salient feature representation and low computational redundancy.
出处
《中国图象图形学报》
CSCD
北大核心
2008年第7期1222-1234,共13页
Journal of Image and Graphics
关键词
计算视觉
火焰
实时警报
视频图像检测
视觉显著性
computer vision, fire/flame, real-time alarm, video fire detection （VFD）, visual attention （VA）
作者简介
杨俊（1976-），男。2007年于国防科技大学电子科学与工程学院获博士学位。主要研究方向为图像分析、理解与信息融合，目标识别。E-mail：yyangjun1234@vip．sina．com
