I was wandering what the best approach would be for detecting 'figures' in an array of 2D points.
In this example I have two 'templates'. Figure 1 is a template and figure 2 is a template. Each of these templates exists only as a vector of points with an x,y coordinate.
Let's say we have a third vector with points with x,y coordinate
What would be the best way to find out and isolate points matching one of the first two arrays in the third one. (including scaling, rotation)?
I have been trying nearest neigbours(FlannBasedMatcehr) or even SVM implementation but it doesn't seem to get me any result, template matching doesn't seem to be the way to go either, I think. I am not working on images but only on 2D points in memory...
Especially because the input vector always has more points than the original data set to be compared with.
All it needs to do is find points in array that match a template.
I am not a 'specialist' in machine learning or opencv. I guess I am overlooking something from the beginning...
Thank you very much for your help/suggestions.