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Categorizing Emails Using Machine Learning with Textual Features Read chapter Read first chapter

2019 | OriginalPaper | Chapter

An Experiment for Background Subtraction in a Dynamic Scene

Authors : Ting-Yuan Lin, Jeng-Sheng Yeh, Fu-Che Wu, Yung-Yu Chuang, Andrew Dellinger

Published in: Advances in Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

This paper aims to analyze a background subtraction algorithm. Different from tradition methods, we feed the trained network with the target and background images. The paper focuses on how to get background images without using the temporal median filter. We use Gaussian mixture models to produce background images. In this way, the accuracy of background images increases. We also study the difference between grayscale and RGB images, and adding the foreground masks from the convolutional Neural Networks to the Gaussian mixture models. Experiments lead on the 2014 ChangeDetection.​net dataset show that our proposed method outperforms several state-of-the-art methods, including IUTIS-5, PAWCS, SuBSENSE and so on.

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Metadata
Title
An Experiment for Background Subtraction in a Dynamic Scene
Authors
Ting-Yuan Lin
Jeng-Sheng Yeh
Fu-Che Wu
Yung-Yu Chuang
Andrew Dellinger
Copyright Year
2019
Book
Advances in Artificial Intelligence

Print ISBN: 978-3-030-18304-2

Electronic ISBN: 978-3-030-18305-9

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-18305-9_39

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