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In this paper we present a novel automatic background substitution approach for live video. The objective of background substitution is to extract the foreground from the input video and then combine it with a new background. In this paper, we use a color line model to improve the Gaussian mixture model in the background cut method to obtain a binary foreground segmentation result that is less sensitive to brightness differences. Based on the high quality binary segmentation results, we can automatically create a reliable trimap for alpha matting to refine the segmentation boundary. To make the composition result more realistic, an automatic foreground color adjustment step is added to make the foreground look consistent with the new background. Compared to previous approaches, our method can produce higher quality binary segmentation results, and to the best of our knowledge, this is the first time such an automatic and integrated background substitution system has been proposed which can run in real time, which makes it practical for everyday applications.


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Practical automatic background substitution for live video

Show Author's information Haozhi Huang1Xiaonan Fang1Yufei Ye1Songhai Zhang1( )Paul L. Rosin2
Department of Computer Science, Tsinghua University, Beijing, 100084, China.
School of Computer Science and Informatics, Cardiff University, Cardiff, CF24 3AA, UK.

Abstract

In this paper we present a novel automatic background substitution approach for live video. The objective of background substitution is to extract the foreground from the input video and then combine it with a new background. In this paper, we use a color line model to improve the Gaussian mixture model in the background cut method to obtain a binary foreground segmentation result that is less sensitive to brightness differences. Based on the high quality binary segmentation results, we can automatically create a reliable trimap for alpha matting to refine the segmentation boundary. To make the composition result more realistic, an automatic foreground color adjustment step is added to make the foreground look consistent with the new background. Compared to previous approaches, our method can produce higher quality binary segmentation results, and to the best of our knowledge, this is the first time such an automatic and integrated background substitution system has been proposed which can run in real time, which makes it practical for everyday applications.

Keywords: alpha matting, background substitution, background replacement, background subtraction

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Revised: 18 August 2016
Accepted: 20 December 2016
Published: 15 March 2017
Issue date: September 2017

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© The Author(s) 2016

Acknowledgements

We thank the reviewers for their valuable comments. This work was supported by the National High-Tech R&D Program of China (Project No. 2012AA011903), the National Natural Science Foundation of China (Project No. 61373069), the Research Grant of Beijing Higher Institution Engineering Research Center, and Tsinghua-Tencent Joint Laboratory for Internet Innovation Technology.

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