#content p.widePar { padding-right: 1em ; } #changes dd { margin-bottom: 1em ; } .award { margin: 1em 0em ; margin-left: 2em ; width: 10em ; font-size: 0.9em ; text-align:center ; float: right ; border: 1px solid #DDD ; background-color: #f6f6f6 ; } #changes .date { font-weight: normal ; font-style: italic ; width: 10em ; }
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 `%env:VERSION;`.

# Download VLFeat %env:VERSION; (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

&nsbp;

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!