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Background Replacement in Video Conferencing
Kiran Shahi*
Yongmin Li
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Submitted: 6 Feb 2023 | Accepted: 24 Apr 2023 | Published: 23 Jun 2023

Abstract

Background replacement is one of the most used features in video conferencing applications by many people, perhaps mainly for privacy protection, but also for other purposes such as branding, marketing and promoting professionalism. However, the existing applications in video conference tools have serious limitations. Most applications tend to generate strong artefacts (while there is a slight change in the perspective of the background), or require green screens to avoid such artefacts, which results in an unnatural background or even exposes the original background to other users in the video conference. In this work, we aim to study the relationship between the foreground and background in real-time videos. Three different methods are presented and evaluated, including the baseline U-Net, the lightweight U-Net MobileNet, and the U-Net MobileNet&ConvLSTM models. The above models are trained on public datasets for image segmentation. Experimental results show that both the lightweight U-Net MobileNet and the U-Net MobileNet& ConvLSTM models achieve superior performance as compared to the baseline U-Net model.

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How to Cite
Shahi, K., & Li, Y. (2023). Background Replacement in Video Conferencing. International Journal of Network Dynamics and Intelligence, 2(2), 100004. https://doi.org/10.53941/ijndi.2023.100004
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Copyright (c) 2023 by the authors.

This work is licensed under a This work is licensed under a Creative Commons Attribution 4.0 International License.

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