面向计算机视觉的吸烟检测方法研究综述

Review of Smoking Detection Methods for Computer Vision

公共场所吸烟严重危害人们身体健康甚至生命财产安全,因此实时高效的吸烟检测具有重要意义。目前基于计算机视觉的吸烟检测以高效率、高精度等优势逐渐成为主流方法。在对非计算机视觉的吸烟检测方法进行简要概述的基础上,重点归纳总结了三类基于计算机视觉的检测方法。探讨了颜色、外观、运动等多种烟雾特征的提取方法;介绍了基于单步骤和多步骤目标检测两种方法提取烟支目标;从人工特征构建、深度学习特征提取角度论述不同类型的吸烟动作特征提取方法。对上述方法进行分析总结并展望未来研究方向。

Smoking in public places seriously harms people’s health and even life and property safety,so real-time and efficient smoking detection is of great significance.At present,smoking detection based on computer vision has gradually become the mainstream method with the advantages of high efficiency and high precision.On the basis of a brief over-view of non-computer vision smoking detection methods,three kinds of detection methods based on computer vision are summarized.Firstly,the extraction methods of smoke features such as color,appearance and movement are discussed.Secondly,two methods of extracting cigarette target based on single step and multi-step target detection are introduced.Finally,different types of smoking action feature extraction methods are discussed from the perspectives of artificial feature construction and deep learning feature extraction.The above methods are analyzed and summarized,and the future research direction is prospected.