This document provides an overview of the Scale Invariant Feature Transform (SIFT) algorithm for feature detection and matching across images. It begins by introducing SIFT and its applications in computer vision. The document then outlines the key steps of the SIFT algorithm, including constructing scale space, approximating the Laplacian of Gaussian, finding keypoints, removing low-contrast keypoints, assigning orientations to keypoints, and generating SIFT features. Details are provided for each step, with examples to illustrate the process. The goal of SIFT is to detect features that are invariant to scale, rotation, illumination and viewpoint changes.