[alexcp_]

Exactly, holds will evolve as they get used and more polished, even indoors. Climbing a Moonboard with a new set of holds is quite different than climbing on one with older more polished holds, even if it's the exact same problem and the same holds.

It's an interesting project and it could be fun to watch, but it's completely useless.

[ethbr1]

Couldn't you reverse-reason about that?

To me, the customer here would be climbing gyms, offering a service to climbers.

   1. Set up camera on routes
   2. Record all climbs
   3. Reason through hold details
   4. Generate potential movements
   5. Show climbs vs ghost movements
   6. Feedback to tune model

3 being accomplished by reasoning "if a movement should be possible using the identified hold, but no one successfully does it, the hold must be misidentified or have different properties."

[alexcp_]

But what is the point? Finding the optimal movements that are needed to complete a climb is not useful if you are not strong enough to execute it.

[ethbr1]

The point in this thread seemed to be "real world holds have different properties, and that defines possible approaches to holds."

To which I pointed out that, with enough data, you could reason backwards to figure out their properties.

Assuming that's solved, if the question is "What is the point?" then I'd answer the same point as golf swing analysis -- structured comparison feedback for continual improvement.

"Have you thought about trying X move at Y point?" or "You're trying X move at Y point, but here's how you differ from someone successfully doing it" both seem useful feedback.

And essentially what's manually generated now, from someone watching and then providing feedback.

With regards to strength, hell, if you wanted to get fancy you could also deduce a specific user's strength, comparing their moves against others' moves on the same features.