Extended scale invariant local binary pattern for background subtraction-Reference-Cited by-同舟云学术

Extended scale invariant local binary pattern for background subtraction

Published:2018-08 Issue:8 Volume:12 Page:1292-1302
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zeng Dongdong¹²³,Zhu Ming¹,Xu Fang¹³,Zhou Tongxue¹³

Affiliation:

1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of SciencesChangchun130033People's Republic of China

2. Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of SciencesChangchun130033People's Republic of China

3. University of Chinese Academy of SciencesBeijing100049People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2016.1026

Reference28 articles.

1. Traditional and recent approaches in background modeling for foreground detection: An overview

2. A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos

3. Background and foreground modeling using nonparametric kernel density estimation for visual surveillance

4. 1999 IEEE Conf. on Computer Vision and Pattern Recognition Fort Collins CO USA C. Stauffer W.E.L. Grimson Adaptive background mixture models for real‐time tracking 246 252

5. 2002 Video‐Based Surveillance Systems Springer Boston MA P. Kaewtrakulpong R. Bowden An improved adaptive background mixture model for real‐time tracking with shadow detection 135 144

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