Are there any differences between cascading classifiers and image pyramid?

Question

I'm currently working on an object detection project and having a bit of a problem on choosing my classifiers.

Answer 1

Image pyramid is a bank of image in different scale, which is wildly used to deal with different object scale in object(face/pedestrian/etc.) detection, while cascade classifier is a ensemble classifier that can be trained to tell positive sample(is face/pedestrian/etc.) from negative sample(background).

Typically, a detection framework could be:

Image -> Image Pyramid -> Slide windows -> Cascade Classifier -> is target or not?