Adaptive background modeling of complex scenarios based on pixel level learning modeled with a retinotopic self-organizing map and radial basis mapping-Reference-Cited by-同舟云学术

Adaptive background modeling of complex scenarios based on pixel level learning modeled with a retinotopic self-organizing map and radial basis mapping

Published:2018-08-14 Issue:12 Volume:48 Page:4976-4997
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Ramirez-Quintana Juan A.^ORCID,Chacon-Murguia Mario I.,Ramirez-Alonso Graciela M.

Funder

TecNM

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/article/10.1007/s10489-018-1256-5/fulltext.html

Reference59 articles.

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3. Bouwmans T (2014) Traditional and recent approaches in background modeling for foreground detection: an overview. Comput Sci Rev 11–12(1):31–66

4. Sobral Vacavant A (2014) A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos. Comput Vis Image Underst 122:4–21

5. Xu Y, Dong J, Zhang B, Xu D (2016) Background modeling methods in video analysis a review and comparative evaluation. CAAI Trans Intell Technol 1(1):3–60

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