Conceptually, if you had an internal 3d model of all objects in CV you could do a scan matching algorithm.

This algorithm would be ridiculously computationally intensive, but it would have a high degree of accuracy (I believe).

I'm wondering if ANN can be used to approximate this internal scan matching in a way that greatly reduces computational load?

For example let's say you have a 3d scan of a car. This car can take a variety of orientations.

One way to do scan matching is pick a bunch of orientations, project to 2d and do a sliding scan match.

Could this entire operation be approximated by a NN which ultimately would have a reduced computational load?


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