Video

Video: How to Optimize Your Live Streaming Workflow

Posted on by Russell Trafford-Jones

Running the live streaming for an event can be fraught, so preparation needs to be the number one priority. In this talk, Robert Reinhardt, a highly experienced streaming consultant takes us through choosing encoders, finding out what the client wanted, helping the client understand what needs to be done, choosing software and ensuring the event stays on air.

This is a wide-ranging and very valuable talk for anyone who’s going to be involved with a live streaming event. In this article, I’ll highlight 3 of the big topics nestled in with the continuous stream of tips and nuances that Rob unearths.

System Architecture. Reliability is usually a big deal for live streaming and this needs to be a consideration not only in the streaming infrastructure in the cloud, but in contribution and the video equipment itself. No one wants to have a failed stream due to a failed camera, so have two. Can you afford a hardware switcher/vision mixer? Rob prefers hardware units in terms of reliability (no random OS reboots), but he acknowledges this is not always practical or possible. Audio, too needs to be remembered and catered for. It’s always better to have black vision and hear the programme than to have silent video. Getting your streams from the event into the cloud can also be done resiliently either by having dual streams into a Wowza server or similar or having some other switching in the cloud. Rob spends some time discussing
whether to use AVC or HEVC, plus the encoder manufacturers that can help.

Discovery and Budget Setting. This is the most important part of Rob’s talk. Finding out what your customer wants to achieve in a structured, well recorded way is vital in order to ensure you meet their expectations and that their expectations are realistic. This discovery process can also be used as a way to take the customer through the options available and decisions that need to be made. For many clients, this discovery process then starts to happen on both sides. Once the client is fully aware of what they need, this can directly feed into the budget setting.

Discovery is more than just helping get the budget right and ensure the client has thought of all aspects of the event, it’s also vital in drawing a boundary around your work and allows you to document your touchpoints who will be providing you things like video, slides and connectivity. Rob suggests using a survey to get this information and offers, as an example, the survey he uses with clients. This part of the talk finishes with Rob highlighting costs that you may incur that you need to ensure are included. Rob has also written up his advice.

Setup and Testing. Much of the final part of the presentation is well understood by people who have done events before and is summarised as ‘test and test again’. But it’s always helpful to have this reiterated and, in this case, from the streaming angle. Rob goes through a long list of what to determine ahead of the event, what to test on-site ahead of the event and again what to test just before the event.

The talk concludes with a twenty minute Q&A.

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Speakers

Robert Reinhardt Robert Reinhardt
CTO,
videoRx

Video: All you need to know about video KPIs

Posted on by Russell Trafford-Jones

KPIs are under the microscope as Milan’s Video Tech meet up fights against the pandemic by having its second event online and focused on measuring, and therefore improving, streaming services.

Looking at ‘Data-Driven Business Decision Making‘, Federico Preli, kicks off the event looking at how to harness user data to improve the user experience. He explains this using Netflix’s House of Cards as an example. Netflix commissioned 2 seasons of House of Cards based not on a pilot, but on data they already have. They knew the British version had been a hit on the platform, they could see that the people who enjoyed that, also watched other films from Kevin Spacey or David Fincher (the director of House of Cards). As such, this large body of data showed that, though success was not guaranteed, there was good cause to expect people to be receptive to this new programme.

Federico goes on to explain how to balance recommendations based upon user data. A balance is necessary, he explains, to avoid a bubble around a viewer where the same things keep on getting recommended and not to exaggerate someone’s interests at the detriment of nuance and not representing the less prominent predilections. He outlines the 5 parts of a balanced recommendations experience: Serendipity, diversity, coverage, fairness & trust. Balancing these equally will provide a rounded experience. Finally, Federico discusses how some platforms may choose to under invest in some of these due to the nature of their platforms. Relevance, for instance, may be less important for an ultra-niche platform where everything has relevance.

‘Performance Video KPIs at the Edge‘ is the topic of Luca Moglia‘s talk. A media solutions engineer from Akamai, he looks at how to derive more KPI information from logs at the edge. Whilst much data comes from a client-side KPI, data directly reported by the video player itself to the service. Client-side information is vital as only the client knows on which button you clicked, for instance and how long you spent in certain parts of the GUI. But in terms of video playback, there is a lot to be understood by looking at the edge, the part of the CDN which is closest to the client.

One aspect that client-side reporting doesn’t cover is use of the platform by clients which aren’t fully supported meaning they report back less information. Alternatively, for some services, it may be possible to access them with clients which don’t report at all. Depending on how reporting is done, this could be blocked by ad blockers or DNS rules. As such, this is an important gap which can be largely filled by analysis of CDN logs. This allows you to enhance the data analysis done elsewhere and validate it.

Luca gives examples of KPIs that can be measured or inferred from the edge, such as ‘hand-waving latency’ which can be understood from the edge-to-origin latency and time to manifest. He also shows an example graph analysing the number of segments served at the edge within the segment duration time. This helps indicate how many streams weren’t rebuffering. Overall, Luca concludes, analysing data from the edge helps track improvements, gives you better visibility on consumer/global events and allows you to enhance the performance of the platform.

Bitmovin’s Andrea Fassina covers ‘Client KPIs – Five Analytics Metrics That Matter‘ which he summarises at the beginning of his talk ahead of explaining each individually. ‘Impressions & Total Hours Watched’ is first. This metric has really shown its importance as the SARS-CoV-2 pandemic has rolled around the globe. Understanding how much more people are watching is important in understanding how your platform is reacting. After all, if a platform is struggling this could be for many reasons that are correlated with, but not because of, more hours streamed. For instance, in boxing matches, it’s often the payment system which struggles before the streaming does.

Video startup time is next. Andrea explains the statistics of lost viewers as your time-to-play increases. You can look at startup time across each device and see where the low-hanging fruit for improvements and prioritise your work. This metric can be extended to ad playing and DRM load time which need to be brought into the overall equation.

Third is Video Bitrate Heatmap which allows you to see which type of chunks are most used and, similarly, which rungs on your ABR ladder aren’t needed (or could be improved.) The fourth KPI discussed is Error Types and Codes. Analysing codes generated can give you early warning to issues and allow you to understand whether you suffer more problems than the industry average (6.6%) but also proactively talk to connectivity providers to reduce problems. Lastly, Andrea explains how Rebuffering percentage helps understand where there are gaps in your service in terms of devices/apps which are particularly struggling.

Source: Andrea Fassina, Bitmovin

‘Video Quality Metrics‘ rounds off the session as Fabio Sonnati tackles the tricky problem of how to know what quality of video each viewer is seeing. Given that the publisher has each and every chunk and can view them, many would think this would mean you could see exactly what each stream would look like. But a streaming service can only see what each chunk looks like on their device in their environment. When you view a chunk encoded at 1080i on an underpowered SD device, what does the user actually see and would they have been better receiving a lower resolution, lower bitrate chunk instead?

In order to understand video quality, Fabio briefly explains some objective metrics such as VMAD, SSIM and PSNR. He then discusses the way that Sky Italia have chosen to create their own metric by combining metrics, subjective feedback and model training. The motivation to do this, to tailor your metric to the unique issues that your platform has to contend with. This metric, called SynthEYE, has been expanded to be able to run without a reference – i.e. it doesn’t require the source as well as the encoded version. Fabio shows results of how well SynthEYE Absolute predicts VMAF and MOS scores. He concludes by saying that using an absolute metric is useful because it gives you the ability to analyse chunk-by-chunk and then match that up with resolution and other analytics data to better understand the performance of the platform.

The session concluded with 20 minutes of Q&A

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Speakers

Luca Moglia Luca Moglia
Media Solutions Engineer,
Akamai
Andrea Fassina Andrea Fassina
Developer Evangelist,
Bitmovin
Fabio Sonnati Fabio Sonnati
Media Architect and
Encoding & Streaming Specialist
Federico Preli Federico Preli
Senior Solution Architect,
ContentWise
Stefano Morello Moderator: Stefano Morello
Senior Sales Engineer,
ContentWise

Video: Broadcast Fundamentals: High Dynamic Range

Posted on by Russell Trafford-Jones

Update: Unfortunately CVP choose to take down this video within 12 hours of this article going live. But there’s good news if you’re interested in HDR. Firstly, you can find the outline and some of the basics of the talk explained below. Secondly, at The Broadcast Knowledge there are plenty of talks discussing HDR! Here’s hoping CVP bring the video back.

Why is High Dynamic Range is like getting a giraffe on a tube train? HDR continues its ascent. Super Bowl LIV was filmed in HDR this year, Sky in the UK has launched HDR and many of the big streaming services support it including Disney+, Prime and Netflix. So as it slowly takes its place, we look at what it is and how it’s achieved in the camera and in production.

Neil Thompson, an Sony Independent Certified Expert, takes a seat in the CVP Common Room to lead us through HDR from the start and explain how giraffes are part of the equation. Dynamic Range makes up two thirds of HDR, so he starts by explaining what it is with an analogy to audio. When you turn up the speakers so they start to distort, that’s the top of your range. The bottom is silence – or rather what you can hear over the quiet hiss that all audio systems have. Similarly in cameras, you can have bright pixels which are a different brightness to the next which represents the top of your range, and the dithering blacks which are the bottom of your range. In video, if you go too bright, all pixels become white even if the subject’s brightness varies which the equivalent of the audio distortion.

With the basic explanation out of the way, Neil moves on to describing the amount or size of dynamic range (DR) which can be done either in stops, contrast ratio or signal to noise ratio. He compares ‘stops’ to a bucket of water with some sludge at the bottom where the range is between the top of sludge and the rim of the bucket. One stop, he explains, is a halving of the range. With the bucket analogy, if you can go half way down the bucket and still hit clear water, you have 1 stop of dynamic range. If you can then go a quarter down with clean water, you have 2 stops. By the time you get to 1/32nd you have 5 stops. If going to 1/64 of the height of the bucket means you end up in the sludge, your system has 5 stops of dynamic range. Reducing the sludge so there’s clear water at 1/64th the height, which in cameras means reducing the noise in the blacks, is one way of increasing the dynamic range of your acquisition.

Update: Unfortunately CVP choose to take down this video within 12 hours of this article going live. But there’s good news if you’re interested in HDR. Firstly, you can find the outline and some of the basics of the talk explained below. Secondly, at The Broadcast Knowledge there are plenty of talks discussing HDR! Here’s hoping CVP bring the video back.

If you would like to know how lenses fit into the equation of gathering light, check out this talk from Cannon’s Larry Thorpe.

Neil looks next at the range of light that we see in real life from sunlight to looking at the stars at night. Our eye has 14 stops of range, though with our iris, we can see the equivalent of 24 stops. Similarly, cameras use an iris to regulate the light incoming which helps move the restricted dynamic range of the camera into the right range of brightness for our shot.

Of course, once you have gathered the light, you need to display it again. Displays’ ability to produce light is measured in ‘nits’, which is the amount of light per metre squared. Knowing how many nits a displays helps you understand the brightness it can show with 1000 nits, currently, being a typical HDR display. Of course, dynamic range is as much about the blacks as the brightness. OLED screens are fantastic at having low blacks, though their brightness can be quite low. LEDs, conversely, Neil explains, can go very bright but the blacks do suffer. You have to also take into account the location of a display device to understand what range it needs. In a dim gallery you can spend longer caring about the blacks, but many places are so bright, the top end is much more important than the blacks.

With the acquisition side explained, Neil moves on to transmission of HDR and it’s like getting a giraffe on a tube train. Neil relates the already familiar ‘log profiles’. There are two HDR curves, known as transfer functions, PQ from Dolby and HLG (Hybrig Log Gamma). Neil looks at which profiles are best for each part of the production workflow and then explains how PQ differs from HLG in terms of expressing brightness levels. In HLG, the brightest part of the signal tells the display device to output as brightly as it can. A PQ signal, however, reserves the brightest signal for 10,000 nits – far higher than displays available today. This means that we need to do some work to deal with the situation where your display isn’t as bright as the one used to master the signal. Neil discusses how we do that with metadata.

Finishing off the talk, Neil takes questions from the audience, but also walks through a long list of questions he brought along including discussing ‘how bright is too bright?’, what to look for in an engineering monitor, lighting for HDR and costs.

Watch now!
Speakers

Neil Thompson Neil Thompson
Freelance Engineer & Trainer

Video: Case Study FIS Ski World Championship

Posted on by Russell Trafford-Jones

There’s a lot to learn when it comes to implementing video over IP, so it’s healthy to stand back from the details and see a working system in use to understand how the theory becomes reality. There’s been a clear change in the tone of conversation at the IP Showcase over the years as we’ve shifted from ‘trust us, this could work’ to ‘this is what it looks like!’ That’s not to say there’s not plenty to be done, but this talk about an uncompressed 2110 remote production workflow is great example of how the benefits of IP are being realised by broadcasters.
Robert Erickson is with Grass Valley specialising in sports such as the FIS Alpine World Ski Championships which were in the city of Åre in Sweden some 600km from Stockholm where Sweden’s public broadcaster SVT is based. With 80 cameras at the championships to be remotely controlled over an uncompressed network, this was no small project. Robert explains the two locations were linked by a backbone of two 100Gbps circuits.

The principle behind SVT’s project was to implement a system which could be redeployed, wouldn’t alter the viewers’ experience and would reduce staff and equipment on site. Interestingly the director wanted to be on-site meaning that the production was then split between much of the staff being in Stockholm, which of course was where most of the equipment was, and Åre. The cameras were natively IP, so no converters were needed in the field.

Centralisation was the name of the game, based in Stockholm, producing an end-to-end IP chain. Network switching was provided by Arista which aggregated the feeds of the cameras and brought them to Stockholm where the CCUs were located. Robert highlights the benefits of this approach which include the use of COTS switches, scalability and indifference as to the circuits in use. We then have a look inside the DirectIP connection which is a 10gig ‘pipe’ carrying 2022-6 camera and return feeds along with control and talkback, replicating the functionality of a SMPTE fibre in IP.

To finish up, Robert talks about the return visions, including multivewers, which were sent back to Åre. A Nimbra setup was used to take advantage of a lower-bandwidth circuit using JPEG 2000 to send the vision back. In addition, it carried the data to connect the vision mixer/switcher at Åre with the switch at Stockholm. This was the only point at which noticeable latency was introduced to the tune of around 4 frames.

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Download the presentation
Speakers

Robert Erickson Robert Erickson
Strategic Account Manager Sports and Venues,
Grass Valley