Density-Based Multifeature Background Subtraction with Support Vector Machine

Background modeling and subtraction is a natural technique for object detection in videos captured by a static camera, and also a critical preprocessing step in various high-level computer vision applications. However, there have not been many studies concerning useful features and binary segmentati...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 34; H. 5; S. 1017 - 1023
Hauptverfasser:	Bohyung Han, Davis, L. S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Los Alamitos, CA IEEE 01.05.2012 IEEE Computer Society
Schlagworte:	Applied sciences Artificial intelligence Background modeling and subtraction Computational modeling Computer science; control theory; systems Convergence Data processing. List processing. Character string processing Density functional theory Exact sciences and technology Haar-like features Image color analysis Kernel kernel density approximation Memory organisation. Data processing Pattern recognition. Digital image processing. Computational geometry Software support vector machine Support vector machines Vectors Computer vision Gradient Segmentation Image processing Video signal Shadow Haar-like features Background modeling and subtraction Haar function Spatial variation Object recognition Modeling Search algorithm Luminance Subtraction support vector machine Scene analysis Object detection Vector support machine Illumination Generative model kernel density approximation
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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