视频和GIS协同的人群状态感知模型

针对监控视频在图像空间难以统一、宏观及真实量化人群状态的问题,提出了一种基于地理信息技术进行人群状态地图展示、量化分析及预警的方法.首先,通过摄像机厂商或标准视频流接口接入监控视频;然后,将视频图像调整为较小尺寸,采用光流法进行计算,获取图像空间下的光流场;最后,将各个监控视频相应的光流场映射至地理空间,即可在地图中观察人群运动状态,并可通过散点内插、等值线等进行分析,通过相关阈值的设置实现人群异常检测与预警.本文基于MATLAB、ArcGIS Engine、C#等技术,采集多个实验视频,并研发了基于GIS的人群状态感知原型系统,对相关算法进行了验证.结果表明,该方法相对于传统图像空间下的人群状态检测方法,具有人群运动可定位、可量测、可宏观观察和预警等优势.

Crowd Status Analysis Based on Surveillance Videos and GIS

In order to solve the problem that surveillance videos were difficult to be unified in the image space and the crowd status was difficult to be perceived macroscopically and quantitatively,a new method was proposed based on GIS,which can be used to display,analyze and early warn crowd status through 2 D map.Firstly,the surveillance video was accessed through the API of camera manufacturers or the standard video stream interface.Secondly,the video images were adjusted to a smaller size and the optical flow field in image space was calculated through some optical calculation algorithm.Finally,the optical flow field of each surveillance video was mapped to the corresponding geographic space.Then through GIS,the movement status of the crowd can be observed in the map.Two analysis methods,including scatter point interpolation and contour map,were put forward.The crowd alarm can be realized through relevant thresholds setting.Based on MATLAB,ArcGIS Engine and Microsoft Visual Studio C#,aprototype system was developed to validate the algorithm using several crowd videos.The results showed that the new method had the advantages of geographic location,measurement,macroscopic observation and early warning,etc.when compared with the previous methods.