SIFT feature (Scale-invariant feature transform, scale-invariant feature transform) is a computer vision algorithm used to detect and describe local features in images. It looks for extreme features in the spatial scale. value points, and extract their position, scale, and rotation invariants. This algorithm was published by David Lowe in 1999 and summarized in 2004. Its application scope includes object recognition, robot map perception and navigation, image stitching, 3D model building, gesture recognition, image tracking and action comparison. This algorithm is patented and the patent owner is the University of British Columbia.