人群行为分析研究综述

Research on Crowd Behavior Analysis: A Review

近年来,人群行为分析成为计算机视觉领域中备受关注的研究方向,主要运用于智能视频监控、人机交互、智能家居、视频检索等领域,以视频中运动人群的行为分析和理解为研究目的,对输入序列图像中的运动目标进行运动检测、匹配和建模.文中对人群行为分析的研究现状以及典型算法进行全面综述.首先对当前人群行为数据库进行简要介绍并分类比较;之后根据人群行为分析算法核心侧重点的不同,将人群行为分析算法分为基于特征和基于模型两大类,并根据每一大类各自的特点进行细分和比较,详细介绍了每类中具有代表性的算法,分析各算法的优缺点和适用的人群场景;最后总结了人群行为分析中的困难和挑战,对该研究领域的发展进行展望.

In recent years,crowd behavior analysis has become one of the hottest research points in computer vision.The main application is intelligent surveillance,human-computer interaction,intelligent household,video retrieval and other fields.It is a primary research goal to analyze behavior,understand crowd in video,execute motion detection,match and model the moving target when input video sequences.This paper summarizes research status,and the state-of-the-art of crowd behavior analysis.Firstly,the database for the current crowd behavior analysis is briefly introduced and compared.Then we classify the algorithm into feature-based and model-based ones according to the difference of the emphasis of crowd behavior analysis core algorithm,meanwhile we subdivide and compare the methods on the basis of respective characteristics of each category,and analyze their advantages,disadvantage and practical crowd scene of the representative algorithm in each category.Finally,we discuss the difficulty and challenge as well as the future research trends of crowd behavior analysis.