I am trying to understand how to extend the idea of one dimensional dynamic time warping to the multidimensional case.
Lets assume I have a dataset with two dimensions where
TrainA holds dimension 1 and
TrainB holds dimension 2. It seems that the simplest case would be
distA = dtw(TrainA) distB = dtw(TrainB) dist = distA + distB // or maybe distA*distB
Is this the right approach? I know there are packages that do this for you but I want to understand what is actually being done.