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# Using Google Cloud AI to measure the physics of U.S. freestyle snowboarding and skiing

**[Google Cloud](https://daily.dev/sources/gcp)** · 6 min read · 0 upvotes · 0 comments

## Summary

Google Cloud built an AI-powered biomechanics tool using Gemini and Google DeepMind computer vision research that extracts full 3D skeletal data from ordinary video footage of freestyle snowboarders and skiers. The system uses quaternion math to measure actual geometric rotation (dubbed 'Rotational Degrees') rather than relying on conventional trick naming, which over-approximates rotation. Analysis of elite athletes like Shaun White revealed consistent gaps between trick names and physical reality — a 1440 may only require ~1,122° of actual body rotation — because corked (tilted-axis) tricks trace shorter diagonal paths through orientation space. This insight helps coaches quantify rotational efficiency and may guide athletes pushing toward quadruple corks.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cloud.google.com/blog/products/ai-machine-learning/measure-physics-of-freestyle-snowboarding-and-skiing/>

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---

Tags: [#gcp](https://daily.dev/tags/gcp), [#computer-vision](https://daily.dev/tags/computer-vision), [#google-gemini](https://daily.dev/tags/google-gemini)

[View this post on daily.dev](https://daily.dev/posts/using-google-cloud-ai-to-measure-the-physics-of-u-s-freestyle-snowboarding-and-skiing-wcfaopbfm)

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