SIFT (Scale-invariant Feature Transform)

Scale-invariant feature transform

The scale-invariant feature transform (SIFT) is a computer vision algorithm that detects, describes, and matches local features in images. It is used in various applications such as object recognition, image stitching, and gesture recognition. SIFT keypoints are extracted from reference images and stored in a database, and then compared to features in new images to identify objects with high confidence.

1 courses cover this concept

CSE 455 Computer Vision

University of Washington

Winter 2022

A general introduction to computer vision, this course covers traditional image processing techniques and newer, machine-learning based approaches. It discusses topics like filtering, edge detection, stereo, flow, and neural network architectures.

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