(I asked this question some time back but got no answers or comments. It's a pretty big question so therefore I thought dividing it into several questions might make it easier to answer. The original thread is here: Matching sets of 3d position data)
Imagine a cube filled with air and ~5000 levitating potatoes. The distance between two potatoes is usually an order of magnitude larger than their diameter and their distribution is pretty random but not normal. The size and number of potatoes in the cube is unknown but I have two methods for measuring it: reference method A (assumed to be the truth), and method B. Both methods have given me the x-, y- and z-position of each potato that it found along with it's size.
QUESTION: The two lists of x-, y-, z- and size data are not in the same order. Is there some method that allows me to assess how well method B measures the size and position of the potatoes without having to determine which two entries in list A and B that refers to the same potato?
If I were to make a method up I might imagine that I plotted the potatoes as blue and red spheres in space (size given by size data) and checked how much of the volume was purple compared to blue or red. But I'd rather use a real method than making something up, and I figure this problem can't possibly be a new one.
method that allows me to assess how well method B measures the size and position of the potatoes
. Of the entire cloud of the potatoes or of each individual potato? If you ask about the latter you have to find a way to identify the same potatoes in the two clouds. $\endgroup$ – ttnphns Nov 27 '14 at 19:21