Congratulations to Professor Kuo for Receiving Technology and Engineering Emmy Award

National Awards Committee’s Technology & Engineering Achievement Committee of the National Academy of Television Arts and Sciences (NATAS) made the announcement on the recipients of the 2020 Technology and Engineering Emmy Award on January 25, 2021. C.-C. Jay Kuo, who is Chair of the APSIPA US Local Chapter and William H. Hogue Professor of Electrical and Computer Engineering, was one of the recipients for his work on “Development of Perceptual Metrics for Video Encoding Optimization.” Professor Kuo had a brief interview on this prestigious recognition.

• You are honored for your work in Development of Perceptual Metrics for Video Encoding Optimization. Can you explain in very basic terms, what exactly this technology is and what it is used for?

This Technology and Engineering Emmy award is the outcome of my research collaboration with Netflix. We developed a new video quality assessment method called VMAF (Video Multimethod Assessment Fusion). VMAF is used by Netflix not only for video quality assessment but also for video encoding optimization. VMAF contributes to high quality streaming video from Netflix as well as other video streaming service providers.

• In just one or two lines, can you share why it’s so important?

Netflix makes VMAF an open-source tool to maximize its impact. It is the de facto standard in video quality assessment for premium video content in video streaming industry.

• If possible, can you share some well-known shows/movies/streaming services that use this technology?

VMAF-optimized encodes have covered the majority of Netflix’s streaming hours today, and VMAF has been used as a quality monitoring tool for almost all of Netflix’s streaming hours. Outside of Netflix, many companies use VMAF as well. The list includes as Twitch, Hostar, Crunchyroll, Tencent Cloud, Billibilli, among others.

• Can you describe how you got this idea and made the breakthrough?

I was lucky to have an opportunity to work with Netflix and generalized the idea of multi-method fusion (MMF) for image quality assessment to VMAF for video quality assessment. I would like to point out that the MMF paper (TIP 2012) was co-authored with my former PhD student, Tsung-Jung Liu, and Professor Weisi Lin. Some basic ideas were developed in that stage. Later on, my former PhD student, Yuchieh Lin, contributed a lot to the generalization from MMF to VMAF with Netflix engineers.