I'm trying to distinguish by code between a real 3D object and its picture - a 2D object, based on depth information.
However the picture (= the 2D image) might be captured from noisy background, so I need something more sophisticated than just having diversified depth information; also, the depth camera's output itself might be noisy and there isn't a straight-forward correlation between the model shape and the depth information.
For example: I have two pairs of color-depth images. One: color/depth pictures of a doll, second: color/depth pictures of a pictured doll. I want to create a flow that for pair no. 1 generates a "yes" output, and for pair no. 2 a "no" output.
Any advice - academical sources as implementation ideas - are very welcome.