DocumentCode :
1796218
Title :
Toward a kindergarten video surveillance system (KVSS) using background subtraction based Type-2 FGMM model
Author :
Abdelhedi, Slim ; Wali, Ali ; Alimi, Adel M.
Author_Institution :
REGIM: Res. Groups in Intell. Machines, Nat. Eng. Sch. of Sfax (ENIS), Sfax, Tunisia
fYear :
2014
fDate :
11-14 Aug. 2014
Firstpage :
440
Lastpage :
446
Abstract :
This paper presents a new video surveillance system called KVSS using background based on Type-2 Fuzzy Gaussian Mixture Models (T2 FGMMs). These techniques are used for resolving some limitations on Gaussian Mixture Models (GMMs) techniques on critical situations like moved camera jitter, illumination changes and objects being introduced or removed from the scene. In this context, we introduce descriptions of T2 GMMs and we present an experimental validation using a new evaluation video dataset which presents various problems. Results demonstrate the relevance of the proposed system.
Keywords :
Gaussian processes; fuzzy set theory; video surveillance; Gaussian mixture model techniques; KVSS; T2 FGMM; background subtraction based type-2 FGMM model; camera jitter; illumination; kindergarten video surveillance system; video dataset; Computational modeling; Filtering; Noise; Noise measurement; Vectors; Video sequences; Video surveillance; Background Subtraction; Human localization; Human tracking; T2 FGMMs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2014 6th International Conference of
Conference_Location :
Tunis
Type :
conf
DOI :
10.1109/SOCPAR.2014.7008047
Filename :
7008047
Link To Document :
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