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A comparative study of algorithms for realtime panoramic video blending

Zhu, Zhe, Lu, Jiaming, Wang, Minxuan, Zhang, Songhai, Martin, Ralph, Liu, Hantao ORCID: and Hu, Shi-Min ORCID: 2018. A comparative study of algorithms for realtime panoramic video blending. IEEE Transactions on Image Processing 27 (6) , pp. 2952-2965. 10.1109/TIP.2018.2808766

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Unlike image blending algorithms, video blending algorithms have been little studied. In this paper, we investigate 6 popular blending algorithms—feather blending, multi-band blending, modified Poisson blending, mean value coordinate blending, multi-spline blending and convolution pyramid blending. We consider their application to blending realtime panoramic videos, a key problem in various virtual reality tasks. To evaluate the performances and suitabilities of the 6 algorithms for this problem, we have created a video benchmark with several videos captured under various conditions. We analyze the time and memory needed by the above 6 algorithms, for both CPU and GPU implementations (where readily parallelizable). The visual quality provided by these algorithms is also evaluated both objectively and subjectively. The video benchmark and algorithm implementations are publicly available1.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 1057-7149
Date of First Compliant Deposit: 22 February 2019
Date of Acceptance: 10 February 2018
Last Modified: 03 May 2023 16:25

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