PEOPLE COUNTING USING COMBINED FEATURE

摘要：

In this paper,we present a new people counting approach in visual surveillance scenes.The features adopted in previous methods are all extracted at pixel-level or based on local area,which are severely affected by factors such as occlusion.To cover the shortage,we introduce a new feature which describes a people crowd as a whole.Because pedestrian behaviors change when the degree of crowdedness varies,we can capture motion information to model a crowd and characterize the pedestrian behaviors based on statistic analysis.Afterwards we combine together the two kinds of features presented above as the final people counting feature.Experiments conducted in real world scenes demonstrate the superior effectiveness of the proposed method.

关键词： people counting macroscopic feature optical flow statistic

作者: Congwen Gao Kaiqi Huang Tieniu Tan

作者单位: National Laboratory of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences

会议类型: 国际会议

会议名称: 第三届全国智能视觉监控学术会议

会议地点: 北京

会议语种:英文

页码: 81-84

在线出版日期: 2011-12-01（万方平台首次上网日期，不代表论文的发表时间）