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FIFA WC Qatar 1st to use Semi Automated Offside Technology - How it works?

Amidst the frenzy over Football World Cup currently underway in Qatar one thins that the fans are wondering about is a number of offsides that referees are so accurately detecting. Read More

Saturday December 3, 2022 2:38 PM, ummid.com with inputs from Agencies

FIFA WC Qatar 1st to use Semi Automated Offside Technology - How it works?

[FIFA TV screen shot]

FIFA World Cup 2022: Amidst the frenzy over Football World Cup currently underway in Qatar one thins that the fans are wondering about is a number of offsides that referees are so accurately detecting.

Semi Automated Offside Technology

A little search revealed that FIFA organisers have deployed Semi Automated Offside Technology (SAOT) for the purpose.

The Artificial Intelligence (AI) based technology that recognizes and tracks players and also the ball, calculating their positions 50 times per second is being used for FIFA World Cup matches first time in Qatar.

SAOT v VAR

[Image: FIFA]

A sensor is attached to the official Qatar 2022 World Cup ball, called Al Rihla — Arabic for "the journey" — allowing SAOT to compare the exact moment it was kicked with the position of the team's last defender and the opposing team's striker, Deutsche Welle (DW), a leading media company based in Germany said in a report.

This level of precision is key for very tight situations in which it's difficult for referees to quickly call offsides. Sometimes a goal and even the result of the whole match can depend on this.

 

Whenever SAOT detects an offside, an alert is sent to the video match officials. They inform the referee, who ultimately has the final say. That's why the system is considered "semi-automated."

Video Assistant Referee

The FIFA organisers had used Video Assistant Referee (VAR) for the 2018 Football Word Cup. SAOT is an advanced version of VAR.

"At the FIFA World Cup in 2018, FIFA took the brave step to use Video Assistant Referee (VAR) technology. Semi-automated offside technology is an evolution of the VAR systems that have been implemented across the world," the world football governing body president Gianni Infantino said.

The data collected by cameras and the ball sensor is processed by Artificial Intelligence (AI) within a few seconds to check the offside situation. Once an offside position is detected, the SAOT system provides an automated offside alert to the video match officials team, reports Xinhua.


After the decision has been confirmed by the VAR and the referee on the pitch, the SAOT then generates a 3D animation to be displayed on the giant screens in the stadium and on TV, which gives the best possible perspectives for an offside situation.

Though being used first in Qatar, the new technology has been successfully trialled at numerous test events including the FIFA Arab Cup 2021 and the FIFA Club World Cup 2021, according to FIFA Director of Football Technology & Innovation Johannes Holzmuller.

Detecting Objects: A Complex Task

The task of making sense of — and extracting valuable information from — video footage is called video analysis, and the artificial intelligence sub-field that deals with that is computer vision.

Imagine that you are a computer, and you can't see the same way humans do. Your eyes are replaced with digital cameras that receive light and transform that information into data. The data tells you how every pixel at every frame appears — for example, how much green, red and blue each pixel has.

This data usually appears as a gigantic table of values. For example, for a 1080p video, where each frame has 1920 x 1080 pixels, each row would have 1920 pixels and each column 1080.
How do you make sense out of this? Well, that's one of the hottest topics in artificial intelligence — object detection and tracking.

How computers recognize people and things

Data scientists have developed different techniques to approach this problem. One is called convolutional neural network (CNN). You can see how this process looks on this website made by Adam Harley, a postdoctoral researcher at Stanford University in the US.

CNNs work by detecting objects layer-by-layer. One way to understand how this works is to think about the process of trying to discern the identity of an object in a pitch-black room.

Using your hands to feel the object, you will ask a series of questions that become increasingly more specific. First you may wonder "Is it rigid or soft?"

You press the object and realize it's hard in some places and softer in others. This movement transforms your understanding of the object: Now you have enough information to know it's something with both soft and hard features. This knowledge would represent the first "layer" of detection. In CNNs, this would be considered the "convolution."

After identifying the first layer, you will ask more questions — like what texture the object has, how big it is or what type of shape it holds. As each of these questions is answered, another layer forms, increasing your overall understanding of what's in front of you. This is close to how CNNs work.

At some point, you will gather enough information to start guessing what the object is. You've gathered that the object is furry, has four legs and ears that stick up from the top of its head. Is it a cat? By now, the CNN would be asking: Is it a player? Or a ball?

In another first, Germany vs Costa Rica FIFA World Cup match held in Qatar on Dec 1 created history for all-female team which took to the pitch as referees. It took 92 years to bring a woman referee to monitor a men's World Cup in FIFA's history.

 

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