Scanning Real-World Object and generating 3D Mesh from it

Question

ARKit app allows us create an ARReferenceObject, and using it, we can reliably recognize a position and orientation of real-world object. But also we can save the finished .arobject file.

However, ARReferenceObject contains only the spatial features information needed for ARKit to recognize the real-world object, and is not a displayable 3D reconstruction of that object.

func createReferenceObject(transform: simd_float4x4, 
                              center: simd_float3, 
                              extent: simd_float3, 
                   completionHandler: (ARReferenceObject?, Error?) -> Void)

My question:

Is there a method that allows us to reconstruct digital 3D geometry (low-poly or high-poly) from .arobject file using Poisson Surface Reconstruction or Photogrammetry?

Answer 1

You answered your own question with a quote from Apple's documentation:

An ARReferenceObject contains only the spatial feature information needed for ARKit to recognize the real-world object, and is not a displayable 3D reconstruction of that object.

If you run that sample code, you can see for yourself the visualizations it creates of the reference object during scanning and after a test recognition — it's just a sparse 3D point cloud. There's certainly no photogrammetry in what Apple's API provides you, and there'd not much to go on in terms of recovering realistic structure in a mesh.

That's not to say that such efforts are impossible — there have been some third parties demoing Here photogrammetry experiments based on top of ARKit. But

1. that's not using ARKit 2 object scanning, just the raw pixel buffer and feature points from ARFrame.

2. the level of extrapolation in those demos would require non-trivial original R&D, as it's far beyond the kind of information ARKit itself supplies.