Two basic questions about icp (iterative closest point) algorithm I am trying to learn shape analysis and a part is learning icp. I have many confusions but for now I have two basic questions:

*

*Does the point clouds need to have the same number of points for icp?

*Does icp needs manual/automatic landmarking?

Thanks.

Although I haven't worked with ICP specifically I have done work with point clouds, hopefully you will get a better answer soon!

*

*I don't think so. Consider a very simple example where you're just fitting a line to a pair of points. The (many) points on the line are each fit to the closest of the two points, and the the line is transformed to minimize this; this is repeated iteratively. (Note: the visual here is just a cartoon, I haven't done any computation to ensure this actually what a single step would look like)




*The more distinct features you can landmark the better, weather it's manually or automatically. Automatic landmarking could be used (and if it works for your application that's great) but manual landmarking, especially if feature of both sets can be exactly match, is going to have a much better chance of forming a tight fit.


