Maximizing the Value of Live Video Streaming with AI

Maximizing the Value of Live Video Streaming with AI

AI forecasts are pretty straightforward – artificial Intelligence spending will very likely be more than $46 billion by 2020.  This will affect many areas, primarily the media industry.

Large amounts of data are becoming available because we spend hours watching live video content or on demand. The next transformative technology will be live video streaming with AI, deep learning and natural language processing (NLP).

All of these will have huge influence on live video streaming starting from content creation to final production. AI is already present in many different industries, so it is expected to be heavily used for live streaming on a wider scale.

At the moment the some of the most prominent names that already leverage AI technology such as Nvidia DLA, IBM Watson etc. mainly deploy it in the cloud with plans to include it in other parts of live streaming.  

Production workforce behind the camera can and will be replaced by artificial intelligence, even time consuming tasks such as data and content management is possible to be performed by AI.

Currently, AI is being used for viewer metrics, network and technical troubleshooting, as well as ad serving. However there are many other potential uses that remain to be tapped.

Live Video Streaming with AI

Right now it is possible for some motion-tracking camera systems to allow automated tracking of moving subjects in front of a camera, but they need producers to position transmitters and/or sensors where needed.

With AI tracking of speakers, entertainers, actors etc. will be possible without any additional sensors. The deep learning algorithms will be capable of analyzing the video and follow people in different positions, on stage or elsewhere, keeping them perfectly framed on camera.   

It is already possible to set up drones to follow athletes when running on a field in order to track targets with greater precision.

You might not think that maths and video storytelling are related in any way but, surprisingly, they are. The video imaging key components such as focal lengths, compositions and frame rates are based on ratios, ratios that require basic math understanding.

In this manner AI-enabled cameras can be optimized to capture videos and images which are pleasing and adequate for the human eye, thus replacing human factors in the process. This means that eventually AI optimized cameras will replace the need for camera crew people altogether in most cases.

Real-Time Video Switching

Real-time video switching will also be affected by AI in the live video streaming process. By using smart software solutions optimum cameras will be selected for various shot and angles depending on the content being streamed.

Using facial and emotional expression, gestures, clothing and color recognition and other imaging data will help the overall real-time video switching process.

This AI software will be able to determine each stream frame, then analyze the audio, video and other aspects of the stream. In other words, the video switchers will be available as auto-mixing features allowing for a full AI production.

Computer vision activated video switchers may be able to work independently on embedded systems or devices. Cameras, in this case, can even leverage a networked cloud server if needed.

Automated Actions in Live Streams

Production events such as conveying a lower-third for a presenter at a certain conference can be possible with facial recognition.

Something called cognitive technology will be dominant in everything from sports to live events.

This will integrate assets and visualizations that change according to specific actions, times, locations, or dynamic data in relation to the live stream.

Natural Language Processing

Natural Language Processing (NLP) is a subfield of Artificial Intelligence that is focused on enabling computers to understand and process human languages, to get computers closer to a human-level understanding of language.

Live transcription, translation, interpretation, captioning, and audio description fto be used in meetings, lectures, or events can have a lot of opportunities for AI development.  

Multinational corporations can benefit from this for live captioning purposes, product launches and general communications in multiple languages for a worldwide audience.

Content Management

The volume of data being generated from video is going to increase because companies will be more involved with live video streaming. The information derived from this data can be used a lot more than what we can extract manually at this time of development.  

We can expect AI to be able to interpret streaming content and extract metadata by descriptive tags, categories, and summaries automatically.

This will open room for more intelligent analytics, content insights, and content management thus paving the way for efficient methods of monetizing video through targeted ads.

Social Media Monitoring

Social media tracking permits brands to gauge online conversations and sentiment analysis, tracking target market response in real time. This allows for immediate customization or adjustment of the content material to match the audience’s said preferences.

Language algorithms will pull records from the live video streaming and seize most important topics and key phrases, after which they will collect screenshots, video scripts, and highlight clips that may be used for advertising functions or routinely uploaded to social media.

Artificial intelligence could be effective for organizations within the streaming industry as soon as they are able to realize its complete potential. We have just started to scratch the surface of the value AI can bring to live video streaming.

With this live content is bound to become different, more engaging as well as cost efficient for the production companies.

AI will propel content material owners, media outlets, and advertisers into a brand new innovative mindset of creating smart and compelling content material.

Maximizing the Value of Live Video Streaming with AI

Maximizing the Value of Live Video Streaming with AI

AI forecasts are pretty straightforward – artificial Intelligence spending will very likely be more than $46 billion by 2020.  This will affect many areas, primarily the media industry.

Large amounts of data are becoming available because we spend hours watching live video content or on demand. The next transformative technology will be live video streaming with AI, deep learning and natural language processing (NLP).

All of these will have huge influence on live video streaming starting from content creation to final production. AI is already present in many different industries, so it is expected to be heavily used for live streaming on a wider scale.

At the moment the some of the most prominent names that already leverage AI technology such as Nvidia DLA, IBM Watson etc. mainly deploy it in the cloud with plans to include it in other parts of live streaming.  

Production workforce behind the camera can and will be replaced by artificial intelligence, even time consuming tasks such as data and content management is possible to be performed by AI.

Currently, AI is being used for viewer metrics, network and technical troubleshooting, as well as ad serving. However there are many other potential uses that remain to be tapped.

Live Video Streaming with AI

Right now it is possible for some motion-tracking camera systems to allow automated tracking of moving subjects in front of a camera, but they need producers to position transmitters and/or sensors where needed.

With AI tracking of speakers, entertainers, actors etc. will be possible without any additional sensors. The deep learning algorithms will be capable of analyzing the video and follow people in different positions, on stage or elsewhere, keeping them perfectly framed on camera.   

It is already possible to set up drones to follow athletes when running on a field in order to track targets with greater precision.

You might not think that maths and video storytelling are related in any way but, surprisingly, they are. The video imaging key components such as focal lengths, compositions and frame rates are based on ratios, ratios that require basic math understanding.

In this manner AI-enabled cameras can be optimized to capture videos and images which are pleasing and adequate for the human eye, thus replacing human factors in the process. This means that eventually AI optimized cameras will replace the need for camera crew people altogether in most cases.

Real-Time Video Switching

Real-time video switching will also be affected by AI in the live video streaming process. By using smart software solutions optimum cameras will be selected for various shot and angles depending on the content being streamed.

Using facial and emotional expression, gestures, clothing and color recognition and other imaging data will help the overall real-time video switching process.

This AI software will be able to determine each stream frame, then analyze the audio, video and other aspects of the stream. In other words, the video switchers will be available as auto-mixing features allowing for a full AI production.

Computer vision activated video switchers may be able to work independently on embedded systems or devices. Cameras, in this case, can even leverage a networked cloud server if needed.

Automated Actions in Live Streams

Production events such as conveying a lower-third for a presenter at a certain conference can be possible with facial recognition.

Something called cognitive technology will be dominant in everything from sports to live events.

This will integrate assets and visualizations that change according to specific actions, times, locations, or dynamic data in relation to the live stream.

Natural Language Processing

Natural Language Processing (NLP) is a subfield of Artificial Intelligence that is focused on enabling computers to understand and process human languages, to get computers closer to a human-level understanding of language.

Live transcription, translation, interpretation, captioning, and audio description fto be used in meetings, lectures, or events can have a lot of opportunities for AI development.  

Multinational corporations can benefit from this for live captioning purposes, product launches and general communications in multiple languages for a worldwide audience.

Content Management

The volume of data being generated from video is going to increase because companies will be more involved with live video streaming. The information derived from this data can be used a lot more than what we can extract manually at this time of development.  

We can expect AI to be able to interpret streaming content and extract metadata by descriptive tags, categories, and summaries automatically.

This will open room for more intelligent analytics, content insights, and content management thus paving the way for efficient methods of monetizing video through targeted ads.

Social Media Monitoring

Social media tracking permits brands to gauge online conversations and sentiment analysis, tracking target market response in real time. This allows for immediate customization or adjustment of the content material to match the audience’s said preferences.

Language algorithms will pull records from the live video streaming and seize most important topics and key phrases, after which they will collect screenshots, video scripts, and highlight clips that may be used for advertising functions or routinely uploaded to social media.

Artificial intelligence could be effective for organizations within the streaming industry as soon as they are able to realize its complete potential. We have just started to scratch the surface of the value AI can bring to live video streaming.

With this live content is bound to become different, more engaging as well as cost efficient for the production companies.

AI will propel content material owners, media outlets, and advertisers into a brand new innovative mindset of creating smart and compelling content material.

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