21 posts tagged with "Computer Vision"

That clip up top: sixty point candidates, one after another, cut automatically out of a 24-minute highlights reel — almost every one starts on a serve.

Watch a tennis broadcast and count how much of it is actually a point being played. Not much. There's a replay after nearly every big rally, a coach's-box shot, a close-up between points — actual tennis is a small slice of the screen. Today's question: can software find, on its own, only the real points inside a whole reel of broadcast footage? It can — and it turned up the best plot twist of the project so far.

That clip up top: both players outlined and tracked, FOREHAND or BACKHAND called out at every swing in the hitter's color, feet moving live on the court diagram — and along the bottom, the shot-by-shot notation typing itself out.

Call a shot forehand or backhand and you're answering a geometry question: which side of the hitter's body did the ball come off? You can't answer that without knowing where the player was standing — and until now, this project had tracked the ball but never found the players. Too much for one sitting: session one of several, starting with finding the players.

That clip up top: the pipeline calling out HIT and BOUNCE in real time, pinning every one onto a court diagram the instant it happens.

The last post ended with a warning that turned into today's homework: the system can only trust the ball's screen position at the exact moments it's touching the court — everything else is guesswork. So today's question: watching nothing but the ball's path across the screen, can software find every hit, and every bounce?

The detector I built today ended up calling all thirteen of those moments correctly. It got there by being wrong twice first, and both mistakes taught me more about how a tennis ball moves than the successes did.

That clip up top: the yellow box tracking the ball on the broadcast picture, next to the same rally redrawn as dots on a plain, top-down court diagram — the ball's real position, in meters, drawn live as the rally plays out.

Last time, the software could hold onto a tennis ball for an entire rally on screen. Today's question: can it tell you whether that ball landed in the court, or a foot wide of it?

That clip up top: an AI following the game ball through a full broadcast rally. The box is the model's answer, not something I added by hand.

Before software can chart a single stroke of tennis, it has to do the simplest thing a ball kid does without thinking: watch the right ball, the whole rally through.