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SIFT Algorithm

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 Detecto r Supports Windows and Linux.

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SIFT Algorithm

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

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

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

  4. Matching Key Points

  5. 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.

  6. 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.

  7. VLFeat’s Key Points and Descriptor

  8. UBC vsVLFeat VLFeat = Blue UBC SIFT = Red Most key points match exactly.

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