Question

hog is simplified version of SIFT ?

Answer 1

solution:

SIFT -  

SIFT descriptor chooses a 16x16 and then divides it into 4x4 windows. Over each of these 4 windows it computes a Histogram of Oriented gradients. While computing this histogram, it also performs an interpolation between neighboring angles. Once you have all the 4x4 windows, it uses a gaussian of half the window size, centered at the center of the 16x16 block to weight the values in the whole 16x16 descriptor.

HOG - HoG on the other hand only computes a simple histogram of oriented gradients as the name says.

I feel that SIFT is more suited in describing the importance of a point, due to the gaussian weighting involved, while HoG does not have such a bias. Due to this reason, (ideally) HoG should be better suited at classification of images over dense SIFT, if all feature vectors are concatenated into one huge vector (this is my opinion, may not be true)

Answer 2

True. Hog is a siplified version of SIFT