专注度识别研究综述  

A Review of Research on Attentiveness Recognition

作　　者：孙帅成 刘瑞明 SUN Shuaicheng;LIU Ruiming(School of Mechanical and Marine Engineering,Jiangsu Ocean University;School of Electronic Engineering,Jiangsu Ocean University,Lianyungang,Jiangsu Province,222005 China)

机构地区：[1]江苏海洋大学机械与海洋工程学院 [2]江苏海洋大学电子工程学院,江苏连云港222005

出　　处：《科技资讯》2021年第4期6-8,39,共4页Science & Technology Information

摘　　要：效率是工作者最关心的问题之一,而专注度是影响效率高低的关键因素。近年来,人们对个人的专注度的重视程度大大提升,提出了很多针对专注度的判断方法,例如人工观察、问卷调查、访谈等。这些方法可信度不高、客观程度不够、效率低下、浪费资源等,在机器视觉快速发展的情况下,将机器视觉和专注度识别相结合,更加智能和高效地进行专注度识别。该文对国内外的研究历程和进展进行了回顾,并从基于人脸表情的专注度识别和基于行为的专注度识别两个方面对人脸专注度识别技术进行了阐述。最后探讨了专注度识别的发展趋势,为后来者提供借鉴。Efficiency is one of the concerns of workers and concentration is a key factor affecting efficiency.In recent years,our emphasis on personal concentration has greatly increased and many judgments on concentration methods such as manual observation,questionnaire surveys,interviews,etc.These methods have low credibility,insufficient objectivity,low efficiency and waste of resources.In the case of rapid development of machine vision,machine vision and concentration recognition are combined to more intelligently and efficiently recognize concentration.This article reviews the research history and progress at home and abroad,and explains the facial recognition technology from two aspects:facial expression-based concentration recognition and behavior-based concentration recognition.Finally,it discusses the development trend of concentration recognition and provides a reference for the latecomers.

关 键 词：专注度 机器视觉 人脸表情识别 行为识别 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]