Features and Regression Techniques for Crowd Density Estimation: A Comparison

Basit Öğe Kaydı
dc.authorid0000-0002-4595-8031en_US
dc.contributor.authorKurnaz, Oğuzhan
dc.contributor.authorHanilçi, Cemal
dc.date.accessioned2021-03-20T20:12:46Z
dc.date.available2021-03-20T20:12:46Z
dc.date.issued2019
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Mekatronik Mühendisliği Bölümüen_US
dc.description11th International Conference on Electrical and Electronics Engineering (ELECO) -- NOV 28-30, 2019 -- Bursa, TURKEYen_US
dc.description.abstractCrowd density estimation is an important problem for the security applications and it is a regression task consisting of feature extraction and regression steps. In this paper, we compare different features and regression techniques for crowd density estimation. To this end 200 images randomly selected from UCSD pedestrian dataset is used in the experiments. Experimental results show that features extracted from gray level co-occurance matrix (GLCM) gives the best performance however the selection of the regression technique depends on the performance criterion. Applying perspective normalization as a pre-processing step and feature elimination as a post-processing step considerably improve the performance.en_US
dc.description.sponsorshipChamber Elect Engineers Bursa Branch, Bursa Uludag Univ, Dept Elect Elect Engn, Istanbul Tech Univ, Fac Elect & Elect Engn, IEEE Turkey Secten_US
dc.identifier.endpage1079en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1075en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/694
dc.identifier.wosWOS:000552654100214en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorKurnaz, Oğuzhan
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2019 11Th International Conference On Electrical And Electronics Engineering (Eleco 2019)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keywords]en_US
dc.titleFeatures and Regression Techniques for Crowd Density Estimation: A Comparisonen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Mekatronik Mühendisliği Bölümü Yayın Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu