Automated AI-based analytics is fast gaining momentum in sports broadcasting, given their benefits to viewing audiences as well as coaches and players. Get insights on the crucial role of embedded cameras and the future of AI and embedded vision in sports broadcasting?

Automated AI based sports broadcasting and analytics has been gaining great popularity in the recent years. With more and more companies coming up with automated sports broadcasting systems, the scope of use cases these devices can cover is also widening. From capturing and broadcasting soccer to golf to basketball matches, there are new use cases emerging every day.

Cameras and embedded vision technology are the heart of any automated sports broadcasting system. Are you wondering what the functions of a camera in such a system are? Do you know whether these cameras are the same as the ones used in professional sports broadcasting?

In this blog, we attempt to answer predominantly these two questions.

What is automated AI-driven sports broadcasting?

Before we look at the role of a camera, we need to understand what AI driven automated sports broadcasting is. To many, the concept still remains unclear.

Automated 스포츠중계 as a term broadly means streaming and broadcasting live sports matches without the help of field operators or crew. Unlike professional sports broadcasting which needs an army of people to operate the camera and associated systems, automated sports broadcasting relies on cameras deployed on the field that automatically sends a feed to be telecast on TV or a streaming platform. These systems do not need any field personnel, and can work reliably during any time of the day irrespective of the weather conditions. Typically, these devices are installed to stream amateur sports matches who cannot afford to have a costly setup to capture them.

Now, where does AI or artificial intelligence come into picture?

While live streaming helps parents, friends, and fans watch amateur matches at the convenience of their homes, AI helps coaches and team managers to evaluate the performance of players and their team, and analyse the tactics of the opponent teams. A video analysis platform developed using AI algorithms helps to analyse match videos to give insights including shot charts, heatmaps and detailed player, team, and game statistics.

Role of cameras in automated sports broadcasting

Cameras predominantly play two roles in an AI driver sports broadcasting system:

• Streaming matches for live broadcasting and viewing
• Serving image and video data for processing and sports based analytics
• Let us now look at each of them in detail.

Streaming matches for live broadcasting and viewing

An automated sports broadcasting system typically involves camera systems mounted on poles around the sports field to capture the complete view of a game. A single camera unit includes multiple cameras (usually 2 to 4 cameras) that work synchronously to capture live videos of a game. This video is sent to a live streaming platform which offers viewers an opportunity to watch a game without having to be physically present in the venue. For the venue owners, this acts as an avenue to increase the number of viewers and popularity of the amateur (or not so popular) tournaments they conduct.

The cameras used in these systems are embedded cameras or camera modules that interface with a host platform – such as NVIDIA Jetson, NXP and Qualcomm etc – for data processing purposes. The camera also comprises of an image sensor, lens, interface, and an ISP (Image Signal Processor).