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Indexed by:会议论文

Date of Publication:2016-01-01

Included Journals:CPCI-S

Key Words:Crowd Density; Prior Knowledge; Perspective correction; Exercise Intensity

Abstract:In recent years, With the development of science and technology to promote the popularity of video surveillance, computer techniques have a great value on obtaining the crowd counting information of surveillance video automatically, but perspective effects, mutual occlusion between people and other factors make crowd counting difficult. This paper presents a crowd counting method on sparse scene. Firstly, analyzing the characteristics of the surveillance video to access available prior knowledge; Secondly, combining with prior knowledge to extract the characteristics of target prospects block; Finally, support vector regression machine is employed to estimate the number. Experiments show that the method improves the situation of pedestrians occlusion crowd counting estimation accuracy.