Hacker News Reader

Comment by davedx | Hacker News Reader

I'd love to hear what the use cases are for this. I was looking at Planet's website yesterday and although the technology is fascinating, I do sometimes struggle to understand what people actually do (commercially or otherwise) with the data? (Genuinely not snark, this stuff's just not my field!)

View on HN

I'm working on a system that uses affordable hardware (iPhones) to make orthopedic surgery easier and more precise. Among other things, we have to track the position in space of surgical tools like drills. Models like this can play a pivotal role in that.

As someone mentioned, this is great for gaussian splatting, which we also do.

My brother is an orthopaedic surgeon, so I’m curious to know more. Do you have a website?

redefinesurgery.com - I'm steve @, would be happy to talk to your brother

This is a super useful utility — until this there was nothing fast and easy that you could dump say 30 quick camera photos of a (room/object/place) into and get out a dense point cloud.

Instead you had to run all these separate pipelines inferring camera location, etc. etc. before you could get any sort of 3D information out of your photos. I’d guess this is going into many many workflows where it will drop in replace a bunch of jury-rigged pipelines.

Architectural visualizations is one. For example, design phase of remodelling your house would be much easier, if you had a 3D reconstruction of the current state already available.

The depth maps and point clouds are useful in CGI to turn a 2D image into a 3D environment which can then be incorporated into a raytracing renderer. E.g. CAD-data based foreground object placed in a generated environment.

Seems like it would provide good data for training control nets for image generation.

This would let you have any of the types if data that this model can output be used as input for controlling image generation.

Collision meshes for Gaussian splats

Reply on news.ycombinator.com