Video: The Evolution of Video APIs

APIs underpin our modern internet and particularly our online streaming services which all. An API is a way for two different programs or services to communicate with each other; allowing access, sharing locations of videos, providing recommendations etc.

Phil Cluff from Mux, takes a look at the evolution of these APIs, showing the simple ones, the complex and how they have changed as time has gone on, culminating in advice to the APIs writers of today and tomorrow.

Security is a big deal and increasingly is in focus for video companies. Whilst the API itself is usually sent over secure means, the service still needs to authenticate users and the use of DRM needs to be considered. Phil talks about this and ultimately the question comes down to what you are trying to protect and your attack surface.

APIs tend to come in two types, explains Phil, Video Platform vs ‘Encoding’ APIs. Encoding APIs a more than pure encoding APIs, there is transcoding, packaging, file transfer and other features built in to most ‘encoding’ services. Video Platform APIs are typically for a whole platform so also include CDN, Analytics, Cataloguing, playback and much more

In terms of advice, Phil explains that APIs can enable ‘normal’ coders – meaning people who aren’t interested specifically in video – to use video in their programs. This can be done through well thought out APIs which make good decisions behind the scenes and use sensible defaults.

API is so important, asserts Phil, that it should be considered as part of the product so treated with similar care. It should be planned, resourced properly, be created as part of a dialogue with customers and, most importantly, revisited later to be upgraded and improved.

Phil finishes the talk with a number of other pieces of advice and answers questions from the floor.

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Speaker

Phil Cluff Phil Cluff
Streaming Specialist,
Mux

Video: Predicting Viewer Attention in Video for use in Compression

Video compression is a never-ending endavour with hundreds of techniques possible. Some which aren’t in use are waiting for computers to catch up or, in this case, to find the best way to apply new techniques, such as machine learning, to the task.

In this talk from Streaming Tech Sweden 2018, Fritz Barnes from Entecon explains that region of interest compression – where you compress the image more in areas where the viewer won’t be looking – can significantly help reduce bitrate.

Fritz looks at techniques to analyse video and work out where people will be looking. This technique is called ‘saliancy deteciton’ and has been made practical by machine learning. Convolutional Neural Networks are introduced. The extensive training material is introduced and explains the model used to learn from it. Optical flow is a way to encode the motion of the video and is also part of the video.

The talk finishes by looking at the results of this technique; both the successes and problems.

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Free registration required
Streaming Tech Sweden is an annual conference run by Eyevinn Technology in Sweden. Talks are recorded and are available to delegates for several months and are then freely available. Whilst registration is required on the website, it is free to register and to watch this video.

Video: A Technical Overview of AV1

If there’s any talk that cuts through the AV1 hype, it must be this one. The talk from the @Scale conference starts by re-introducing AV1 and AoM but then moves quickly on to encoding techniques and the toolsets now available in AV1.

Starting by looking at the evolution from VP9 to AV1, Google engineer Yue Chen looks at:

  • Extended Reference Frames
  • Motion Vector Prediction
  • Dynamic Motion Vector Referencing
  • Overlapped Block Motion Compensation
  • Masked Compound Prediction
  • Warped Motion Compensation
  • Transform (TX) Coding, Kernels & Block Partitioning
  • Entropy Coding
  • AV1 Symbol Coding
  • Level-map TX Coefficient Coding
  • Restoration and Post-Processing
  • Constrained Dire. Enhancement Filtering
  • In-loop restoration & super resolution
  • Film Grain Synthesis

The talk finishes by looking at Compression Efficiency of AV1 against both HEVC (x.265) & VP9 (libvpx) then coding complexity in terms of speed plus what’s next on the roadmap!

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Speaker

Yue Chen Yue Chen
Senior AV1 Engineer,
Google

Video: Per-Title Encoding, @Scale Conference

Per-title encoding with machine learning is the topic of thie video from MUX.

Nick Chadwick explains that rather than using the same set of parameters to encode every video, the smart money is to find the best balance of bitrate and resolution for each video. By analysing a large number of combinations of bitrate and resolution, Nick shows you can build what he calls a ‘convex hull’ when graphing against quality. This allows you to find the optimal settings.

Doing this en mass is difficult, and Nick spends some time looking at the different ways of implementing it. In the end, Nick and data scientist Ben Dodson built a system which optimses bitrate for each title using neural nets trained on data sets. This resulted in 84% of videos looking better using this method rather than a static ladder.

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Speaker

Nick Chadwick Nick Chadwick
Software Engineer,
Mux