Reference : LaBGen: A method based on motion detection for generating the background of a scene
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/203572
LaBGen: A method based on motion detection for generating the background of a scene
English
Laugraud, Benjamin mailto [Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore) >]
Pierard, Sébastien mailto [Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications >]
Van Droogenbroeck, Marc mailto [Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications >]
2017
Pattern Recognition Letters
Elsevier Science
96
Special Issue on Scene Background Modeling and Initialization
12-21
Yes (verified by ORBi)
International
0167-8655
[en] Background generation ; Background initialization ; Background subtraction ; Motion detection ; Median filter ; SBI dataset ; LaBGen ; SBMI ; SBMC
[en] Given a video sequence acquired with a fixed camera, the generation of the stationary background of the scene is a challenging problem which aims at computing a reference image for a motionless background. For that purpose, we developed our method named LaBGen, which emerged as the best one during the Scene Background Modeling and Initialization (SBMI) workshop organized in 2015, and the IEEE Scene Background Modeling Contest (SBMC) organized in 2016. LaBGen combines a pixel-wise temporal median filter and a patch selection mechanism based on motion detection. To detect motion, a background subtraction algorithm decides, for each frame, which pixels belong to the background. In this paper, we describe the LaBGen method extensively, evaluate it on the SBI 2016 dataset and compare its performance with other background generation methods. We also study its computational complexity, the performance sensitivity with respect to its parameters, and the stability of the predicted background image over time with respect to the chosen background subtraction algorithm. We provide an open source C++ implementation at http://www.telecom.ulg.ac.be/labgen.
Montefiore Institute of Electrical Engineering and Computer Science - Montefiore Institute
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/203572
10.1016/j.patrec.2016.11.022
http://www.telecom.ulg.ac.be/labgen

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Laugraud2017LaBGen.pdfAuthor postprint11.64 MBView/Open

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.