SIFT Algorithm Scale-invariant feature transform Extracts features that are robust to changes in image scale, noise, illumination, and local geometric.

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Presentation transcript:

SIFT Algorithm Scale-invariant feature transform Extracts features that are robust to changes in image scale, noise, illumination, and local geometric distortion

University of British Columbia David Lowe’s patented method Demo Software: SIFT Keypoint Detector Supports Windows and Linux

UBC’s Key Interest Points Key locations are defined as maxima and minima of the result of difference of Gaussians function applied in scale-space to a series of smoothed and resampled images.

Matching Key Points

VLFeat Open source library with popular algorithms including SIFT, MSER, k-means, hierarchical k- means, agglomerative information bottleneck, and quick shift. Written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use and detailed documentation throughout. It supports Windows, Mac OS X, and Linux.

VLFeat Key point is a disk of center f(1:2), scale f(3) and orientation f(4). Descriptors are a green grid centered on the key point.

VLFeat’s Key Points and Descriptor

UBC vs VLFeat VLFeat = BlueUBC SIFT = RedMost key points match exactly.