Counting crowd flow based on feature points

A counting approach for crowd flow based on feature points is proposed. The objective is to obtain the characteristics of the crowd flow in a scene, including the crowd orientation and numeric count. For the feature point detection, a three-frame difference algorithm is used to obtain a foreground c...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 133; S. 377 - 384
Hauptverfasser:	Liang, Ronghua, Zhu, Yuge, Wang, Haixia
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 10.06.2014 Elsevier
Schlagworte:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Artificial intelligence Clustering Computer science; control theory; systems Counting Data processing. List processing. Character string processing DBSCAN clustering algorithm Exact sciences and technology Hessian matrix Mathematical analysis Memory organisation. Data processing Optical flow Orientation Pattern recognition. Digital image processing. Computational geometry Software Statistics Support vector regression Surf SURF feature point Theoretical computing Three-frame difference Tracking Support vector regression SURF feature point Three-frame difference Optical flow DBSCAN clustering algorithm Hessian matrix Cluster analysis Image matching Algorithm complexity Vector support machine Hessian matrices Computer vision Data analysis Statistical analysis Crowd Cluster Regression analysis Orientation Experimental result ABackground Scene flow Scene analysis Time complexity Counting Moving body
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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