title: What is the difference between dense SIFT and HoG?
body: <p>I am new to Computer Vision. I am studying Dense SIFT and HOG. For dense SIFT, the algorithm just considers every point as an interesting point and computes its gradient vector. HOG is another way to describe an image with a gradient vector.</p>
  
  <p>I think Dense SIFT is a special case for HOG. In HoG, if we set the bin size to 8, for each window there are 4 blocks, for each block, there are 4 cells and the block stride is the same as the block size, we can still get a 128 dim vector for this window. And we can set any window stride to slide the window to detect the whole image. If the window stride of both these two algorithms is the same, they can get identical results.</p>
  
  <p>I am not sure whether I am correct. Can anyone help me?</p>