Variational Bayesian learning for background subtraction based on local fusion feature

Variational Bayesian learning for background subtraction based on local fusion feature

To resist the adverse effect of shadow interference, illumination changes, indigent texture and scenario jitter in object detection and improve performance, a background modelling method based on local fusion feature and variational Bayesian learning is proposed. First, U‐LBSP (uniform‐local binary...

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Bibliographic Details
Main Authors: Junhua Yan, Shunfei Wang, Tianxia Xie, Yong Yang, Jiayi Wang
Format: Article
Language:English
Published: Wiley 2016-12-01
Series:IET Computer Vision
Subjects:
variational Bayesian learning
background subtraction
shadow interference effect
illumination changes
indigent texture
scenario jitter
Online Access:https://doi.org/10.1049/iet-cvi.2016.0075

Internet

https://doi.org/10.1049/iet-cvi.2016.0075

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