Deep learning impact on video streaming challenges
Source – https://www.techiexpert.com/
After a long day at work, you are dazed but at the same time determined to watch the newest episodes of your favourite series. And just when you’re in the nail-biting scene, the video has paused, then begins to buffer and never resumes! After a few frustrating seconds later, the video is at its lowest resolution, hardly showing clarity.
How did an exhilarating affair end into an arduous one?
Say Hello, to Video Streaming challenges. Honestly, This is not how a video should be streaming. That is when the potential game-changers like AI and Deep Learning comes into action. They can ensure Zero-delay, High Definition, enhanced streaming OTT making the user experience more enjoyable and worthy.
OTT or Over the Top content makers, as well as the providers, are launching intriguing content every single week. But the Quality of experience which is generally referred to as QoE is one main issue that’s not been able to tackle well enough by the OTT platforms.
QoE is about a video’s overall resolution, startup time, stalls and pauses that happen through the relay. Seamless delivery of video is highly reliable on internet speed or the so-called bandwidth which can drastically affect the user experience. That is when this ABR comes into play tackling the challenges with an innovative algorithm.
The parameters of a video have been “adapted” dynamically by the performance of your network. Therefore, compromising the quality of the video. But, it is still dependent on internet speed. It is 2021, and a lot of talks is happening around Deep Learning.
Videos have been the new type of data communication, literally an extension to an email or text. This has created a necessity for developments in video streaming with optimization of network and data. Most of the happening these days are unperceptive to the content it holds. The bitrate of a scene where the characters are just having a conversation differs from that of an action scene. Imagine seeing the wrinkles on Dumbledore’s face when he raises his wand, but unable to see clearly when Harry is fighting Voldemort.
And that needs an answer to the following questions
- What if a scene’s content could be comprehended?
- What if streaming algorithms learn the QoE by every scene?
- What if the encoding is instructed with relative importance to all frames?
- What if the streaming is friendly on any device?
The best possible answer is Deep Learning.
Artificial Intelligence and Deep Learning are advancing technologies to improve video content and user’s QoE. Content conscious AI can remarkably improve the viewing experience making it personalized, immersive and novel. DNN (Deep Neutral Network) can be made device-aware, dynamically computing it with the strategic resources to scale up the performance of streaming.
An intelligent and notable method to enhance QoE is when the encoder looks at the entire video than looking at the pixels in individual frames. This helps for
- A better understanding of content
- Delivering the highest quality stream
- Identifying the content redundancies.
How can the impact of Deep Learning take place?
The device quality plays a major role in the entire process of decoding. Making it device friendly by all means, says that people can watch it anytime, anywhere and by any device. A click on the app of their smartphones. Because smartphones are the new laptops. Having the track on which device is targeted by the user can make his/her personal experience most engaging. The unique potential of a device can be utilized as its soul ability to redefine the entire streaming.
It doesn’t end there at being device-aware. Deep Learning and Artificial Intelligence can be made to pay specific attention to the entire context of the video, search preferences, genre interest. For instance, a user is streaming a particular series every week. Deep learning can use this data to show the user the preference show, the similar genres, other shows from the director and cast. This not only improves the QoE of the user but also makes it a Win-Win for the OTT providers as well.
Understanding the business of Streaming
One might wonder why an OTT platform has to invest in such user engaging technologies? The answer to this is a recent survey done across 1000 customers who are using the OTT streaming in Urban India. As many as 62% of people viewing through the OTT face issues like buffering, pausing and hang of the app whilst used on travelling.
More than ever, In recent times, the customers are making it clear by immediate feedbacks on official and social media sites regarding any dissatisfaction While using the OTT. This shows a clear intolerance in regards to lower QoE which can affect the revenue. Long load times, buffering, pixelation and stalled videos should no longer be seen to sustain this business.
The emerging trends, the pandemic situation has given new dynamics to online streaming. The limitations to short films or fiction videos have widened up to live stream of sports, gaming and releasing movies. Thereby generating more revenue.
Gone were the days of gaming with Personal Computers. But, games like PUBG having pulled greater crowds just from a smartphone. The new gaming platform from Google, stadia gave an announcement stating as low bandwidth as 25mbps is enough for exceptional streaming.
This tells us how cost-effective ideas are emerging to change the phase of this business using AI and deep learning. A recent survey showed that 53.98% of viewers were willing to upgrade to premium subscriptions for intriguing content that has minimal streaming challenges.
Finally, The big picture of delivering high-quality videos at lower cost subscriptions to generate greater revenues is in view. The considerable benefits obtained from the usage of AI and the impact of deep learning in creating a greater streaming experience has solved many practical conditions. The biggest innovations of all this process are DNN based advancements. So, very soon this is going to change all the demographics to matchless QoE and incredible video consumption.