Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.
Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of wildlife and match moving.
The algorithm is patented in the US; the owner is the University of British Columbia.
Read more about Scale-invariant Feature Transform: Overview, Features, Comparison of SIFT Features With Other Local Features
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