Open Access Open Access  Restricted Access Subscription or Fee Access

People Counting System with H_mk Segmentation in Dense Crowd Views

H. H. Lin, K. T. Win

Abstract



Crowd People counting in dense crowd scenes is a difficult task due to various appearance, perspective distortions and severe occlusions. Most of the previous works degrade the performance due to illuminations, and inter-class variations. The more the performance result increased, the more accurate the foreground segment need to have. To avoid these issues, this proposed work contributes an H_mk segmentation algorithm for accurate foreground segmentation. This work also proposes an effective people counting framework by using mean subtraction background estimation for clear background, H_mk segmentation and deep convolutional neural network (CNN) that exactly estimates the person number. Performance results are evaluated on challenging crowd counting dataset that gets the significant performance than the previous works.

Keywords


Mean subtraction background, H_mk segmentation, deep CNN, crowd counting.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.