I have a few indoor map construction algorithms and the ground truth map. I am trying to compare their construction accuracies w.r.t. the ground truth map.
Like any other scientific evaluations, mere visual comparisons are not enough. I need to quantize the errors so that I can claim which one is superior.
I am only interested in the corridors. So basically by construction accuracy, I mean how accurately the corridors (the corridor walls) are constructed. So I am indifferent about the room walls, etc.
I find this not easy, because this problem lie in between image processing and graph theory. On the one hand, I cannot simply compare the two images with image processing techniques, because I am not interested those trivial details mentioned above. On the other hand, the constructed map is not a collection of vertices and edges. So graph theory may not work here, either.
I have thought about overlapping the constructed on over the ground truth and see how well they are overlapped. A problem with this is what if my constructed map is of a slightly different scale with the original one? Then they will overlap very poorly, albeit the constructed map is actually ok.
So is there any good standard way of comparing two indoor maps?
Ground truth is the background floor map. The red curve is what the algorithm constructs. I wish to compare and quantify the construction errors. (The thickness of the red curve is only for visual purposes. It is actually a deterministic mathematically expressed curve)