The Scale Invariant Feature Transform (SIFT) is a method to detect
distinctive, invariant image feature points, which easily can be
matched between images to perform tasks such as object detection
and recognition, or to compute geometrical transformations between
images. The open-source SIFT library available here is implemented
in C using the OpenCV open-source computer vision library and
includes functions for computing SIFT features in images, matching
SIFT features between images using kd-trees, and computing
geometrical image transforms from feature matches using RANSAC.
The library also includes functionality to import and work with
image features from both
Lowe's SIFT executable and
Oxford VGG’s affine covariant feature detectors. The images
below depict some of this functionality.
detected in two images
matched between the two images and the transform computed
from the matches using RANSAC.
Please see the THANKS file in the distribution for a list of
contributors. Many thanks to all of these folks.
patent has been issued for methods embodied in this software:
"Method and apparatus for identifying scale invariant
features in an image and use of same for locating an object
in an image," David G. Lowe, US Patent 6,711,293 (March 23,
2004). Provisional application filed March 8, 1999. Asignee:
The University of British Columbia. For further details,
contact David Lowe
(firstname.lastname@example.org) or the
University-Industry Liaison Office of the University of