CASIA OpenIR  > 智能感知与计算研究中心
People counting using combined feature
Congwen Gao; Kaiqi Huang; Tieniu Tan
2011
Conference Name2011 Third Chinese Conference on Intelligent Visual Surveillance
Source PublicationConference on Intelligent Visual Surveillance, 2011
Pages81–84
Conference Date2011
Conference PlaceBeijing, China
AbstractIn 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.
KeywordStatistical Analysis   video Surveillance   combined Feature
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12698
Collection智能感知与计算研究中心
Corresponding AuthorKaiqi Huang
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Congwen Gao,Kaiqi Huang,Tieniu Tan. People counting using combined feature[C],2011:81–84.
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