Video: Line by Line Processing of Video on IT Hardware

If the tyranny of frame buffers is let to continue, line-latency I/O is rendered impossible without increasing frame-rate to 60fps or, preferably, beyond. In SDI, hardware was able to process video line-by-line. Now, with uncompressed SDI, is the same possible with IT hardware?

Kieran Kunhya from Open Broadcast Systems explains how he has been able to develop line-latency video I/O with SMPTE 2110, how he’s coupled that with low-latency AVC and HEVC encoding and the challenges his company has had to overcome.

The commercial drivers are fairly well known for reducing the latency. Firstly, for standard 1080i50, typically treated as 25fps, if you have a single frame buffer, you are treated to a 40ms delay. If you need multiple buffers for a workflow, this soon stacks up so whatever the latency of your codec – uncompressed or JPEG XS, for example – the latency will be far above it. In today’s covid world, companies are looking for cutting the latency so people can work remotely. This has only intensified the interest that was already there for the purposes of remote production (REMIs) in having low-latency feeds. In the Covid world, low latency allows full engagement in conversations which is vital for news anchors to conduct interviews as well as they would in person.

IP, itself, has come into its own during recent times where there has been no-one around to move an SDI cable, being able to log in and scale up, or down, SMPTE ST 2110 infrastructure remotely is a major benefit. IT equipment has been shown to be fairly resilient to supply chain disruption during the pandemic, says Kieran, due to the industry being larger and being used to scaling up.

Kieran’s approach to receiving ST 2110 deals in chunks of 5 to 10 lines. This gives you time to process the last few lines whilst you are waiting for the next to arrive. This processing can be de-encapsulation, processing the pixel values to translate to another format or to modify the values to key on graphics.

As the world is focussed on delivering in and out of unusual and residential places, low-bitrate is the name of the game. So Kieran looks at low-latency HEVC/AVC encoding as part of an example workflow which takes in ST 2110 video at the broadcaster and encodes to MPEG to deliver to the home. In the home, the video is likely to be decoded natively on a computer, but Kieran shows an SDI card which can be used to deliver in traditional baseband if necessary.

Kieran talks about the dos and don’ts of encoding and decoding with AVC and HEVC with low latency targetting an end-to-end budget of 100ms. The name of the game is to avoid waiting for whole frames, so refreshing the screen with I-frame information in small slices, is one way of keeping the decoder supplied with fresh information without having to take the full-frame hit of 40ms (for 1080i50). Audio is best sent uncompressed to ensure its latency is lower than that of the video.

Decoding requires carefully handling the slice boundaries, ensuring deblocking i used so there are no artefacts seen. Compressed video is often not PTP locked which does mean that delivery into most ST 2110 infrastructures requires frame synchronising and resampling audio.

Kieran foresees increasing use of 2110 to MPEG Transport Stream back to 2110 workflows during the pandemic and finishes by discussing the tradeoffs in delivering during Covid.

Watch now!
Speaker

Kieran Kunhya Kieran Kunhya
CEO & Founder, Open Broadcast Systems

Video: Super Resolution: What’s the buzz and why does it matter?

“Enhance!” the captain shouts as the blurry image on the main screen becomes sharp and crisp again. This was sci-fi – and this still is sci-fi – but super-resolution techniques are showing that it’s really not that far-fetched. Able to increase the sharpness of video, machine learning can enable upscaling from HD to UHD as well as increasing the frame-rate.

Bitmovin’s Adithyan Ilangovan is here to explain the success they’ve seen with super-resolution and though he concentrates on upscaling, this is just as relevant to improving downscaling. Here are our previous articles covering super resolution.

Adithyan outlines two main enablers of super resolution, allowing it to displace the traditional methods such as bicubic and Lanczos. Enabler one is the advent of machine learning which now has a good foundation of libraries and documentation for coders allowing it to be fairly accessible to a wide audience. Furthermore, the proliferation of GPUs and, particularly for mobile devices, neural engines is a big help. Using the GPUs inside CPUs or in desktop PCI slots allows the analysis to be done locally without transferring great amounts of video to the cloud solely for the purpose of processing or identification. Furthermore, if your workflow is in the cloud, it’s now easy to rent GPUS and FPGAs to handle such workloads.

Using machine learning doesn’t only allow for better upscaling on a frame-by-frame basis, but we are also able to allow it to form a view of the whole file, or at least whole scene. With abetter understanding of the type of video it’s analysing (cartoon, sports, computer screen etc.) it can tune the upscaling algorithm to deal with this optimally.

Anime has seen a lot of tuning for super resolution. Due to Anime’s long history, there are a lot of old cartoons which are both noisy and low resolution which are still enjoyed now but would benefit from more resolution to match the screens we now routinely used.

Adithyan finishes by asking how we should best take advantage of super resolution. Codecs such as LCEVC use it directly within the codec itself, but for systems which have pre and post-processing before the encoder, Adithyan suggests it’s viable to consider reducing the bitrate to reduce the CDN costs knowing the using super-resolution on the decoder, the video quality can actually be maintained.

The video ends with a Q&A.

Watch now!
Download the slides
Speaker

Adithyan Ilangovan Adithyan Ilangovan
Encoding Engineer,
Bitmovin

Video: Outlook on the future codec landscape

VVC has now been released, MPEG’s successor to HEVC. But what is it? And whilst it brings 50% bitrate savings over HEVC, how does it compare to other codecs like AV1 and the other new MPEG standards? This primer answers these questions and more.

Christian Feldmann from Bitmovin starts by looking at four of the current codecs, AVC, HEVC, VP9 and AV1. VP9 isn’t often heard about in traditional broadcast circles, but it’s relatively well used online as it’s supported on Android phones and brings bitrate savings over AVC. Google use VP9 on Youtube for compatible players and see a higher retention rate. Netflix and Twitch also use it. AV1 is also in use by the tech giants, though its use outside of those who built it (Netflix, Facebook etc.) is not yet apparent. Christian looks at the compatibility of the codecs, hardware decoding, efficiency and cost.

Looking now at the other upcoming MPEG codecs, Christian examines MPEG-5 Essential Video Coding (EVC) which has two profiles: Baseline and Main. The baseline profile only uses technologies which are old enough to be outside of patent claims. This allows you to use the codec without the concern that you may be asked for a fee from a patent holder who comes out of the woodwork. The main profile, however, does have patented technology and performs better. Businesses which wish to use this codec can then pay licences but if an unexpected patent holder appears, each individual tool in the codec can be disabled, allowing you to protect continue using, albeit without that technology. Whilst it is a shame that patents are so difficult to account for, this shows MPEG has taken seriously the situation with HEVC which famously has hundreds of licensable patents with over a third of eligible companies not part of a patent pool. EVC performs 32% better than AVC using the baseline profile and 25% better than HEVC with the main profile.

Next under the magnifying glass is Low Complexity Enhancement Video Coding (LCEVC). We’ve already heard about this on The Broadcast Knowledge from Guido, CEO of V-Nova who gave a deeper look at Demuxed 2019 and more recently at Streaming Media West. Whilst those are detailed talks, this is a great overview of the technology which is actually a hybrid approach to encoding. It allows you to take any existing codec such as AVC, AV1 etc. and put LCEVC on top of it. Using both together allows you to run your base encoder at a lower resolution (say HD instead of UHD) and then deliver to the decoder this low-resolution encode plus a small stream of enhancement information which the decoder uses to bring the video back up to size and add back in the missing detail. The big win here, as the name indicates, is that this method is very flexible and can take advantage of all sorts of available computing power in embedded technology as and in servers. In set-top boxes, parts of the SoC which aren’t used can be put to use. In phones, both the onboard HEVC decoding chip and the CPU can be used. It’s also useful in for automated workflows as the base codec stream is smaller and hence easier to decode, plus the enhancement information concentrates on the edges of objects so can be used on its own by AI/machine learning algorithms to more readily analyse video footage. Encoding time drops by over a third for AVC and EVC.

Now, Christian looks at the codec-du-jour, Versatile Video Codec (VVC), explaining that its enhancements over HEVC come not just from bitrate improvements but techniques which better encode screen content (i.e. computer games), allow for better 360 degree video and reduce delay. Subjective results show up to 50% improvement. For more detail on VVC, check out this talk from Microsoft’s Gary Sullivan.

The talk finishes with answers so audience questions: Which will be the winner, what future device & hardware support will be and which is best for real-time streaming.

Watch now!
Speakers

Christian Feldmann Christian Feldmann
Team lead, Encoding,
Bitmovin

Video: Futuristic Codecs and a Healthy Obsession with Video Startup Time

These next 12 months are going to see 3 new MPEG standards being released. What does this mean for the industry? How useful will they be and when can we start using them? MPEG’s coming to the market with a range of commercial models to show it’s learning from the mistakes of the past so it should be interesting to see the adoption levels in the year after their release. This is part of the second session of the Vienna Video Tech Meetup and delves into startup time for streaming services.

In the first talk, Dr. Christian Feldmann explains the current codec landscape highlighting the ubiquitous AVC (H.264), UHD’s friend, HEVC (H.265), and the newer VP9 & AV1. The latter two differentiate themselves by being free to used and are open, particularly AV1. Whilst slow, both the latter are seeing increasing adoption in streaming, but no one’s suggesting that AVC isn’t still the go-to codec for most online streaming.

Christian then introduces the three new codecs, EVC (Essential Video Coding), LCEVC (Low-Complexity Enhancement Video Coding) and VVC (Versatile Video Coding) all of which have different aims. We start by looking at EVC whose aim is too replicate the encoding efficiency of HEVC, but importantly to produce a royalty-free baseline profile as well as a main profile which improves efficiency further but with royalties. This will be the first time that you’ve been able to use an MPEG codec in this way to eliminate your liability for royalty payments. There is further protection in that if any of the tools is found to have patent problems, it can be individually turned off, the idea being that companies can have more confidence in deploying the new technology.

The next codec in the spotlight is LCEVC which uses an enhancement technique to encode video. The aim of this codec is to enable lower-end hardware to access high resolutions and/or lower bitrates. This can be useful in set-top boxes and for online streaming, but also for non-broadcast applications like small embedded recorders. It can achieve a light improvement in compression over HEVC, but it’s well known that HEVC is very computationally heavy.

LCEVC reduces computational needs by only encoding a lower resolution version (say, SD) of the video in a codec of your choice, whether that be AVC, HEVC or otherwise. The decoder will then decode this and upscale the video back to the original resolution, HD in this example. This would look soft, normally, but LCEVC also sends enhancement data to add back in the edges and detail that would have otherwise been lost. This can be done in CPU whilst the other decoding could be done by the dedicated AVC/HEVC hardware and naturally encoding/decoding a quarter-resolution image is much easier than the full resolution.

Lastly, VVC goes under the spotlight. This is the direct successor to HEVC and is also known as H.266. VVC naturally has the aim of improving compression over HEVC by the traditional 50% target but also has important optimisations for more types of content such as 360 degree video and screen content such as video games.

To finish this first Vienna Video Tech Meetup, Christoph Prager lays out the reasons he thinks that everyone involved in online streaming should obsess about Video Startup Time. After defining that he means the time between pressing play and seeing the first frame of video. The longer that delay, the assumption is that the longer the wait, the more users won’t bother watching. To understand what video streaming should be like, he examines Spotify’s example who have always had the goal of bringing the audio start time down to 200ms. Christophe points to this podcast for more details on what Spotify has done to optimise this metric which includes activating GUI elements before, strictly speaking, they can do anything because the audio still hasn’t loaded. This, however, has an impact of immediacy with perception being half the battle.

“for every additional second of startup delay, an additional 5.8% of your viewership leaves”

Christophe also draws on Akamai’s 2012 white paper which, among other things, investigated how startup time puts viewers off. Christophe also cites research from Snap who found that within 2 seconds, the entirety of the audience for that video would have gone. Snap, of course, to specialise in very short videos, but taken with the right caveats, this could indicate that Akamai’s numbers, if the research was repeated today, may be higher for 2020. Christophe finishes up by looking at the individual components which go towards adding latency to the user experience: Player startup time, DRM load time, Ad load time, Ad tag load time.

Watch now!
Speakers

Christian Feldmann Dr. Christian Feldmann
Team Lead Encoding,
Bitmovin
Christoph Prager Christoph Prager
Product Manager, Analytics
Bitmovin
Markus Hafellner Markus Hafellner
Product Manager, Encoding
Bitmovin