SIFT is a feature extraction algorithm in computer vision. It is designed to detect and describe local features in images that are invariant to image scale, rotation, and illumination changes. SIFT works by identifying keypoints in an image, which are locations with distinctive characteristics. These keypoints are then described by a set of features that can be used for tasks like object recognition, image stitching, and 3D model construction. SIFT has been widely used in various applications, from autonomous driving (for object detection) to image retrieval systems.
