Home
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

- VLFeat 0.9.21 (Windows, Mac, Linux)
- Source code and installation
- repository, bug tracking.

# 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

- Caltech-101 classification
- SIFT matching for auto-stitching
- All 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!