Video: Running live video with FFmpeg

San Francisco Video Tech welcomes Haluk Ucar talking about live video streaming. How do you encode multiple resolutions/bitrates efficiently on CPUs and maximise the amount of channels? Is there value in managing multiple encodes centrally? How can we manage the balance between CPU use and VQ?

Haluk discusses a toolset for Adaptive Decisions and looks at Adaptive Segment Decisions. Here he discusses the relationship between IDR frames and frequent Scene Changes.

Haluk covers a lot and finishes with a Q&A. So if you have an interest in Live Streaming, then Watch Now!

Speaker

Haluk Ucar Haluk Ucar
Director of Engineering,
IDT

Video: VP9 Transcoding for Live eSports Broadcast

VP9 is a well-known codec, but it hasn’t seen many high-profile, live deployments which makes Twitch’s move to deliver their platform using VP9 in preference over AVC all the more interesting.

Here, Yueshi Shen from Twitch, explains the rationale for VP9 by explaining the scale of Twitch and looking at their AVC bitrate demands. He explains the patent issues with HEVC and VP9 then looks at decoder support across devices and platforms. Importantly, encoder implementation is examined leading to Twitch’s choice of FPGA to provide live encoding.

Yueshi then looks at the potential of AV1 to Switch_Frame to provide low-latency broadcast at scale.

Watch now!

Speaker

Yueshi Shen Yueshi Shen
Principal (Level 7) Research Engineer & Engineering Manager,
Twitch

Video: The state of advanced codecs; separating hype from reality

There are a lot of codecs both new and old that are in use or vying to be the next big thing. Tom Vaughan helps us see what they really can achieve and where each one is useful.

Recorded at San Francisco Video Tech Meetup in September, this video starts with a look at a the ‘hype cycle’. Tom places each codec, from MPEG 2 to VVC on the curve before looking at what the barriers to adoption are.

Tom then looks at HEVC discussing which devices can receive it, which can create it, the streaming services which support it and where adoption is likely to be. Finally, HEVC discussion is complete without a look at the HEVC patent landscape Venn diagram.

The focus then shifts to the Alliance for Open Media and their AV1 codec, its patent status and technical progress to date. He then discusses the performance of AV1, HEVC and Beamr against each other.

Almost brand new out of the starting blocks is VVC from MPEG and the Media Coding Industry Forum (MC-IF). Tom explains the aims of the forum and the VVC codec they are creating before taking questions from the floor.

Watch now!

Speaker

Tom Vaughan Tom Vaughan
VP Strategy,
Beamr

Video: Scalable Video Coding in HEVC & AV1

While it has never played a big role in practical applications, scalable video coding has been around since the times of MPEG 2, and might actually have some advantages over the multi-rate transmission often applied today. The purpose of scalable coding is to efficiently compress multiple different versions of the same video in one “scalable” bitstream. Actually this sounds like the perfect solution for VOD and streaming applications, but unfortunately it has some downsides and few vendors ever used it. In this talk, Chrstian will review the basic idea of scalable coding, how it is enabled in modern coding standards and the pros and cons of implementing the technology in streaming applications.

Speaker

Christian Feldmann Chrisitan Feldmann
Codec Engineer,
Bitmovin

Video: VMAF – the Journey Continues

VMAF is a video quality metric created by Netflix which allows computers to indicate what quality a video is. This is an important part of evaluating how good your encoder or streaming service is so it’s no surprise that Netflix has invested years of research into this. Other metrics such as PSNR and MS-SSIM all have their problems – and let’s accept that no metric is perfect – but what the industry has long grappled with is that a video that has a strong fidelity to the source doesn’t necessarily look better than one that less-faithfully replicates the source.

Imagine you had a video of an overcast day and one encoder rendered the video a bit brighter and a bit more blue. Well, for that clip, people watching might prefer that encoder even though the video is quite different from the source. The same is true of noisy pictures where replicating the noise isn’t always the best idea as some people, for some content, would prefer the cleaner look even though some details may have been lost.

As such, metrics have evolved from PSNR which is much more about fidelity to metrics which try harder to model what ‘looks good’ and VMAF is an example of that.

Zhi Li explains the history of VMAF and explains some of the new features which were released in August 2018, when this talk was given, which gives an insight into the way VMAF works. Plus, there’s a look ahead at new features on the road map. This talk was given at a SF Video Technology meet up.

Watch now!

Speakers

Zhi Li Zhi Li
Senior Software Engineer – Video Algorithms and Research
Netflix