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Proceedings Paper

Efficient measurement of quality at scale in Facebook video ecosystem
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Paper Abstract

This paper describes FB-MOS metric that measures video quality at scale in Facebook ecosystem. As the quality of uploaded UGC source itself varies widely, FB-MOS consists of both a no-reference component to assess input (upload) quality and a full-reference component, based on SSIM, to assess quality preserved in the transcoding and delivery pipeline. Note that the same video may be watched on a variety of devices (Mobile/laptop/TV) in varying network conditions that cause quality fluctuations; moreover, the viewer can switch between in-line view and full-screen view during the same viewing session. We show how FB-MOS metric accounts for all this variation in viewing condition while minimizing the computation overhead. Validation of this metric on FB-content has shown that SROCC is 0.9147 using internally selected videos. The paper also discusses some of the optimizations to reduce metric computation complexity and scale the complexity in proportion to video popularity.

Paper Details

Date Published: 21 August 2020
PDF: 12 pages
Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115100J (21 August 2020);
Show Author Affiliations
Shankar L. Regunathan, Facebook Inc. (United States)
Haixiong Wang, Facebook Inc. (United States)
Yun Zhang, Facebook Inc. (United States)
Yu (Ryan) Liu, Facebook Inc. (United States)
David Wolstencroft, Facebook Inc. (United States)
Srinath Reddy, Facebook Inc (United States)
Cosmin Stejerean, Facebook Inc. (United States)
Sonal Gandhi, Facebook Inc. (United States)
Minchuan Chen, Facebook Inc. (United States)
Pankaj Sethi, Facebook Inc. (United States)
Amit Puntambekar, Facebook Inc. (United States)
Mike Coward, Facebook Inc. (United States)
Ioannis Katsavounidis, Facebook Inc. (United States)


Published in SPIE Proceedings Vol. 11510:
Applications of Digital Image Processing XLIII
Andrew G. Tescher; Touradj Ebrahimi, Editor(s)

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