Key
Vector that summarizes the content of the keypoint neighborhood
invariance
- scale
- normalize keypoints to be the same size
- rotation
- We are given a keypoint and its scale from DoG (SIFT - local detector)
- We will select the direction of maximum Image gradient as the orientation for the keypoint
- We will describe all features relative to this orientation
SIFT - local detector Descriptor
generating vector from rotated patch
One (bad) approach
- We can turn every pixel into a histogram
- Histogram contains 8 buckets, all of them zero except for one.
- Make the bucket of the direction of the gradient equal to 1
- produces sparse vectors
- Solution:
- divide keypoint up into 4x4 “cells”
- Calculate a histogram per cell and sum them together
SIFT Descriptor
- scale and rotation invariant
