# SIFT

2019-07-03

Computer Vision

389

Useful Materials
Distinctive Image Features from Scale-Invariant Keypoints[1] by David G. Lowe.
SIFT(Scale-Invariant Feature Transform)[2] on Towards Data Science.
The SIFT (Scale Invariant Feature Transform) Detector and Descriptor[3].
Notes
Uses DoG (Difference of Gaussian) to approximate Scale-normalized LoG (Laplacian of Gaussian)[4].
where is the two dimensions Gaussian function, and is the input image.
[need more consideration] After each octave, the Gaussian image is down-sampled by a factor of 2, by resampling the Gaussian image that has twice the initial value of by taking every second pixel in each row and column. And we start on the new octave with .
Since the image size is reduced to 1/4, the sigma for the next octave becomes , which is equal to .
To understand it, frist consider this question: If the image size is reduced to 1\4, but the kernel size of