Automatic Estimation of Crowd Density Using Texture

This paper considers the problem of automatic estimation of crowd densities, an important part of the problem of automatic crowd monitoring and control. A new technique based on texture description of the images of the area under surveillance is proposed. Two methods based on different approaches of texture analysis, one statistical and another spectral, are applied on real images captured in an area of Liverpool Street Railway Station, London, UK. The results obtained show that both methods present similar general rates of correct estimation, and that the potential use of texture description for the problem of automatic estimation of crowd densities is encouraging.