[en] Over the last few years, a wide variety of background subtraction algorithms have been proposed for the detection of moving objects in videos acquired with a static camera. While much effort have been devoted to the development of robust background models, the automatic spatial selection of useful features for representing the background has been neglected. In this paper, we propose a generic and tractable feature selection method. Interesting contributions of this work are the proposal of a selection process coherent with the segmentation process and the exploitation of global foreground models in the selection strategy. Experiments conducted on the ViBe algorithm show that our feature selection technique improves the segmentation results.
Research Center/Unit :
Department of Electrical Engineering and Computer Science (Montefiore Institute), Signal and Image Exploitation (INTELSIG)
Disciplines :
Computer science
Author, co-author :
Braham, Marc ; Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Van Droogenbroeck, Marc ; Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Language :
English
Title :
A Generic Feature Selection Method for Background Subtraction Using Global Foreground Models
Publication date :
October 2015
Event name :
Advanced Concepts for Intelligent Vision Systems (ACIVS)
Event place :
Catania, Italy
Event date :
26-29 October 2015
Audience :
International
Main work title :
Advanced Concepts for Intelligent Vision Systems (ACIVS), Catania 26-29 October 2015
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