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22 July 2017
Paper published in a book (Scientific congresses and symposiums)
Is a Memoryless Motion Detection Truly Relevant for Background Generation with LaBGen?
Laugraud, Benjamin  ; Van Droogenbroeck, Marc 
2017 • In Advanced Concepts for Intelligent Vision Systems
Peer reviewed
 

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Keywords :
Background generation; Background initialization; Background subtraction; Optical flow; Motion detection; Median filter; SBI dataset; SBMnet dataset; LaBGen; LaBGen-OF
Abstract :
[en] The stationary background generation problem consists in generating a unique image representing the stationary background of a given video sequence. The LaBGen background generation method combines a pixel-wise median filter and a patch selection mechanism based on a motion detection performed by a background subtraction algorithm. In our previous works related to LaBGen, we have shown that, surprisingly, the frame difference algorithm provides the most effective motion detection on average. Compared to other background subtraction algorithms, it detects motion between two frames without relying on additional past frames, and is therefore memoryless. In this paper, we experimentally check whether the memoryless property is truly relevant for LaBGen, and whether the effective motion detection provided by the frame difference is not an isolated case. For this purpose, we introduce LaBGen-OF, a variant of LaBGen leverages memoryless dense optical flow algorithms for motion detection. Our experiments show that using a memoryless motion detector is an adequate choice for our background generation framework, and that LaBGen-OF outperforms LaBGen on the SBMnet dataset. We further provide an open-source C++ implementation of both methods at http://www.telecom.ulg.ac.be/labgen.
Research center :
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège
Telim
Disciplines :
Electrical & electronics engineering
Computer science
Author, co-author :
Laugraud, Benjamin ;  Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore)
Van Droogenbroeck, Marc  ;  Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Language :
English
Title :
Is a Memoryless Motion Detection Truly Relevant for Background Generation with LaBGen?
Publication date :
September 2017
Event name :
Advanced Concepts for Intelligent Vision Systems (ACIVS)
Event place :
Belgium
Event date :
from 18-09-2017 to 21-19-2017
Audience :
International
Main work title :
Advanced Concepts for Intelligent Vision Systems
Collection name :
Lecture Notes in Computer Science, volume 10617
Pages :
443-454
Peer reviewed :
Peer reviewed

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