From 6-22 February, the 2026 Winter Olympics in Milan-Cortina d’Ampezzo, Italy will feature not just the world’s top winter athletes but also some of the most advanced sports technologies today. At the first Cortina Olympics in 1956, the Swiss company Omega—based in Biel/Bienne—introduced electronic ski starting gates and launched the first automated timing tech of its kind.
At this year’s Olympics, Swiss Timing, sister company to Omega under the parent Swatch Group, unveils a new generation of motion analysis and computer vision technology. The new technologies on offer include photofinish cameras that capture up to 40,000 images per second.
“We work very closely with athletes,” says Alain Zobrist, CEO of Swiss Timing, Omega’s sister company within the Swatch Group, who has overseen Olympic timekeeping since the winter games of 2006 in Torino “They are the primary customers of our technology and services, and they need to understand how our systems work in order to trust them.”
Using high-resolution cameras and AI algorithms tuned to skaters’ routines, Milan-Cortina Olympic officials expect new figure skating tech to be a key highlight of the games. Omega
Figure Skating Tech Completes the Rotation
Figure skating, the Winter Olympics’ biggest TV draw, is receiving a substantial upgrade at Milano Cortina 2026.
Fourteen 8K resolution cameras positioned around the rink will capture every skater’s movement. “We use proprietary software to interpret the images and visualize athlete movement in a 3D model,” says Zobrist. “AI processes the data so we can track trajectory, position, and movement across all three axes—X, Y, and Z”.
The system measures jump heights, air times, and landing speeds in real time, producing heat maps and graphic overlays that break down each program—all instantaneously. “The time it takes for us to measure the data, until we show a matrix on TV with a graphic, this whole chain needs to take less than 1/10 of a second,” Zobrist says.
A range of different AI models helps the broadcasters and commentators process each skater’s every move on the ice.
“There is an AI that helps our computer vision system do pose estimation,” he says. “So we have a camera that is filming what is happening, and an AI that helps the camera understand what it’s looking at. And then there is a second type of AI, which is more similar to a large language model that makes sense of the data that we collect”.
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