Background subtraction using infinite asymmetric Gaussian mixture models with simultaneous feature selection

Mixture models are broadly applied in image processing domains. Related existing challenges include failure to approximate exact data shapes, estimate correct number of components, and ignore irrelevant features. In this study, the authors develop a statistical self‐refinement framework for the back...

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Detalhes bibliográficos

Principais autores:	Ziyang Song, Samr Ali, Nizar Bouguila
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Wiley 2020-09-01
coleção:	IET Image Processing
Assuntos:	variational inference methods uninformative features background subtraction task infinite asymmetric Gaussian mixture models simultaneous feature selection image processing domains
Acesso em linha:	https://doi.org/10.1049/iet-ipr.2019.1029
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