ACM OpenSource Award

The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is 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. The latest version of VLFeat is 0.9.21.

Download

Documentation

MATLAB commands
C API with algorithm descriptions
Command line tools

Tutorials

Features: Covariant detectors, HOG, SIFT, MSER, Quick shift, SLIC
Clustering: IKM, HIKM, AIB
Matching: Randomized kd-trees
All tutorials

Example applications

Citing

@misc{vedaldi08vlfeat,
 Author = {A. Vedaldi and B. Fulkerson},
 Title = {{VLFeat}: An Open and Portable Library
          of Computer Vision Algorithms},
 Year  = {2008},
 Howpublished = {\url{http://www.vlfeat.org/}}
}

Acknowledgments

UCLA Vision Lab Oxford VGG.

News

8/1/2018 VLFeat 0.9.21 released: Maintenance release. Fixed vl_argparse to be compatible with MatConvNet. Fixed the binaries for recent versions of macOS.
14/1/2015 VLFeat 0.9.20 released: Maintenance release. Bugfixes.
12/9/2014 MatConvNet: Looking for an easy-to-use package to work with deep convolutional neural networks in MATLAB? Check out our new MatConvNet toolbox!

VLFeat.org