It was easily doable for even more years using plain and boring MK1 eyeballs and a stopwatch.

If you are spending millions on ads, you can pay a couple of guys to watch TV and take notes.

Broadcasters also keep logs of their broadcasts for verification purposes. The traffic systems that inject the ads have parameters for how often and what times certain ads are played which are quite deterministic.

For the World Cup, this was always easy.

It was not easy for your local triple A baseball game being streamed to 500 viewers. This approach scales down.

Hours of bleeding-edge CV analysis sounds pretty expensive for a triple-A game streamed to 500 pairs of eyeballs. They’ll be using the pen & paper approach, too.

Not at scale - a thousand games automatically scored: easy, just feed in the new video files. A thousand workers for individual matches across the country and different channels: absolutely not.

Not to mention human accuracy will likely be way, way worse, no human being will maintain their attention counting ads at five second intervals for even ten minutes, almost two hours is unthinkable.

If attention is all you have, humans are pretty bad at it for long boring tasks.

Since people have bought air time on a broadcast, people have done this very thing to ensure their ad ran. They also notice other analytics like what other ads ran around it and what the content of the program was when it ran. Can't run an ad selling a new car when the scene just before the break was a brutal car wreck or something.

Eventually, people buying ad time on TV stations could request an air check and receive a VHS tape showing a bit of the programming before/after the ad pod your ad ran. Particularly useful when buying ad time on local stations out of the market where you lived.

I remember google bought a company that recorded local FM broadcasts around the country to independently verify ad plays.

I worked for a company in 2020 that did ad analysis with computer vision - specifically in sports, quantifying value for sponsors based on exposure on team socials (accounting for logo size, positioning, etc in photos + videos) - I was a humble annotator https://www.blinkfire.com

Plain and boring computer vision would have still required a team who would identify frames to sample before processing, and then annotate, generalize and classify the data.

Not an expert on this but I don't think same kind of manual effort is required anymore.

It was never required because you already had the frames labeled. Because you gave the ad footage to the station. You created the ad, you already have a golden copy, you just need to verify N sequential frames match to within X percent of pixels.

> by using plain and boring computer vision

Technology is funny, I remember when an intern project detected cats in Youtube videos and it was front page news (round here, at least).

Now it's just boring technology.

>"You're flying! You're sitting in a chair, in the sky!" --PP toucher CK.

This goes along well with another saying I have.

"You will never prove machines are intelligent, you will only prove humans are not"

You probably don't even need vision. The audio on adverts is noticeably different.

There's no audio on the adverts in question.

> The analysis counted advertising built into the match footage (e.g. on the hoardings), rather than commercials shown during advertising breaks