FIFA World Cup 2022 track Players with AI for Offside Calls

FIFA, the global governing body of association football, has revealed it will use AI-powered cameras to assist referees in making offside calls at the 2022 World Cup.

The semi-automated approach consists of a sensor in the ball that dispatches its assignment on the field 500 terms a second, and 12 tracking cameras climbed under the roof of stadiums, which use machine learning to follow 29 points in players’ bodies.

The software will connect this data to generate automated alerts when players commit offside offenses. Alerts will be shipped to officials in a nearby control room, who will validate the decision and advise referees on the field on what call to make.

FIFA claims this procedure will happen “within a few seconds and means that offside decisions can be made quickly and more accurately.” In addition, the data developed by the cameras and ball will also be used to create automated animations, which can be recreated on screens in the stadium and in TV broadcasts “to notify all spectators in the most obvious possible way” of why the call was assembled.

The latest model of FIFA AI embracing sports is automated technology to assist referees in making decisions. FIFA previously raised VAR, or the video assistant referee, permitting referees to review decisions using sideline monitors at the 2018 World Cup.

Chairman of the FIFA Referees Committee, Pierluigi Collina, said the new system would permit officials to make “faster and more accurate decisions” but emphasized that humans — not “robots” — were still in control of the game.

“I know that someone called it ‘robot offside’; it’s not,” told Collina. “The referees and the assistant referees are still accountable for the decision on the field of play.”

Stated FIFA president Gianni Infantino: “This technology is the culmination of three years of reliable research and testing to provide the very best for the teams, players, and fans, and FIFA is proud of this work as we look ahead to the world seeing the advantages of semi-automated offside technology at the FIFA World Cup 2022.”

The 2022 World Cup will happen in Qatar, making it the first to be hosted in an Arabic country. In addition, the tournament will be held from November to December instead of in the summer, as is tradition to offset the heat of Qatar.

The decision to host the World Cup in Qatar has been strongly criticized. An investigation by the United States Department of Justice found that top FIFA officials had been bribed to award the tournament to the Arab country.

Numerous investigations by organizations like Human Rights Watch and The Guardian also found that Qatar’s stadiums have been built by migrant workers who are essentially enslaved — their passports confiscated and their salaries suspended. An investigation in 2021 found that at least 6,500 migrant workers have died in Qatar due to extreme working conditions since the country was awarded the World Cup in 2010.

The first four games of the 2022 World Cup will be played on November 21st, including England vs. Iran and USA vs. Wales.

AI is becoming so ubiquitous that it’s rare to spot a smartphone without some AI. “AI camera” is the new hot term that audiences keep hearing at the takeoff of the latest smartphones, especially the intermediate and high-end ones. For that reason alone, it’s worth understanding what AI in cameras does and how it helps numerous facets of life – even law enforcement!

Artificial Intelligence is a computer science component that tries to teach a computer to think, learn, and perform tasks like a human. Instead of being coded to do a particular job, high-powered electronic appliances are packed with the power of AI, which does not merely instruct it to do a specific job, but programs it such that it understands and adapts to the user’s behavior and patterns. For example, AI cameras are simply cameras that use AI programs to sell images and videos wisely.


Computational photography is generally the core of an AI-powered camera. The subject of computational photography is usually split into subsets of technology trying to emulate what humans do, like voice-to-text composition, voice recognition, image/face recognition, computer vision, and machine learning.

These advanced cameras save time by smartly performing the requisite image processing/enhancement in real-time, which would otherwise need hours of toiling with the image on Photoshop or Lighthouse—commercial-grade photo editing software.

iPhone 12 owners probably use the face unlock feature. This face unlocking ability is an AI program. Aside from pricey iPhones, even the cheaper Android smartphones now include a face unlock feature. Face unlocking studies the face of the end-user and recognizes it. It even learns about transitions in the face, so if you completely shave your beard or go for a spirited summer look after years of dreadlocks, it will still tend to recognize you and unlock your mobile if you happen to be its owner. Moreover, it understands those changes so that your face doesn’t go unnoticed.

Face recognition is fast evolving as the de-facto authentication method for biometrics applications. Aided by depth-sensing sensors, the level of safety delivered by this technology has fulfilled the expectations even in high-security settings and applications like banking. In addition, creating secure runtime environments (programs and libraries) has led to growing trust in the technology at the user level. As a result, people are now happily taking this tech in smartphones, not to cite the many companies working to execute this tech in other domains, including cars, residences, and surveillance applications.

Google has an immense amount of data that has been accumulated over the years, and artificial intelligence is conditional on the abundance of data. As a result, Google is miles ahead of its competitors, given its vast ocean of user data. Furthermore, this data enables the tech giant to develop accurate computational algorithms that make the camera powerful, something other phones can only become when supplemented with additional hardware, i.e., multiple camera lenses, specialized sensors, etc.

Google Pixel uses sophisticated AI technology that quickly makes up for the smartphone’s lack of a dual lens. As a result, its camera cannot only create the bokeh effect but can also do some optical zooming. Although many mobile cameras give the bokeh effect without additional lenses, being able to simulate an optical zoom without hardware is genuinely fantastic.