Dynamically Learning Haar Cascade (in OpenCV)
Sadly, I don't know of any simple way to achieve this, for Haar cascades.

The problem is that Haar cascades are trained using boosting.  A cascade is a multi-stage classifier: we use the first stage to quickly discard candidates: if the first stage says "no", we immediately reject, and only go on to process the input with the second stage if the first stage says "yes".  That means that the second stage is trained on only images that the first stage classifies "yes".  If you add some more training examples and want to update the first stage, then now this has cascading effects on all of the subsequent stages: naively, you need to re-train all subsequent stages, because the set of images they should be trained on has now changed.

There might be a clever way to do it, but it's not straightforward.