VLFeat (Vision Library Features)
                            Version 0.9.18

ABOUT

  The VLFeat open source library implements popular computer vision
  algorithms including SIFT, MSER, k-means, hierarchical k-means,
  agglomerative information bottleneck, and quick shift. 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.

  VLFeat is distributed under the BSD license (see the COPYING file).

  The documentation is available online at
  http://www.vlfeat.org/index.html. A copy of the same is shipped with
  the library in doc/index.html. See also:

  * Installing VLFeat permanently in MATLAB: http://www.vlfeat.org/install-matlab.html
  * Using the command line utilities: http://www.vlfeat.org/install-shell.html
  * Linking to your C program: http://www.vlfeat.org/install-c.html
  * Compiling from source: http://www.vlfeat.org/compiling.html

QUICK START WITH MATLAB

  To start using VLFeat as a MATLAB toolbox, download the latest
  VLFeat binary package from http://www.vlfeat.org/download/. Note
  that the pre-compiled binaries require MATLAB 2009B and
  later. Unpack it, for example by using WinZIP (Windows), by double
  clicking on the archive (Mac), or by using the command line (Linux
  and Mac):

  > tar xzf vlfeat-X.Y.Z-bin.tar.gz

  Here X.Y.Z denotes the latest version. Start MATLAB and run the
  VLFeat setup command:

  > run VLFEATROOT/toolbox/vl_setup

  Here VLFEATROOT is the path to the VLFeat directory created by
  unpacking the archive. All VLFeat demos can now be run in a row by
  the command:

  > vl_demo

OCTAVE SUPPORT

  The toolbox should be laregly compatible with GNU Octave, an open
  source MATLAB equivalent. However, the binary distribution does not
  ship with pre-built GNU Octave MEX files. To compile them use

  > cd <vlfeat directory>
  > MKOCTFILE=<path to the mkoctfile program> make

CHANGES

  0.9.18     Several bugfixes. Improved documentation, particularly
             of the covariant detectors. Minor enhancements of
             the Fisher vectors.

  0.9.17     Rewritten SVM implementation, adding support for SGD and
             SDCA optimisers and various loss functions (hinge,
             squared hinge, logistic, etc.) and improving the
             interface. Added infrastructure to support multi-core
             computations using OpenMP (MATLAB 2009B or later
             required). Added OpenMP support to KD-trees and
             KMeans. Added new Gaussian Mixture Models, VLAD encoding,
             and Fisher Vector encodings (also with OpenMP
             support). Added LIOP feature descriptors. Added new
             object category recognition example code, supporting
             several standard benchmarks off-the-shelf.

  0.9.16     Added VL_COVDET(). This function implements the following
             detectors: DoG, Hessian, Harris Laplace, Hessian Laplace,
             Multiscale Hessian, Multiscale Harris. It also implements
             affine adaptation, estiamtion of feature orientation,
             computation of descriptors on the affine patches
             (including raw patches), and sourcing of custom feature
             frame.

  0.9.15     Added VL_HOG() (HOG features). Added VL_SVMPEGASOS() and
             a vastly improved SVM implementation. Added IHASHSUM (hashed
             counting). Improved INTHIST (integral histogram). Added
             VL_CUMMAX(). Improved the implementation of VL_ROC() and
             VL_PR(). Added VL_DET() (Detection Error Trade-off (DET)
             curves). Improved the verbosity control to AIB. Added
             support for Xcode 4.3, improved support for past and
             future Xcode versions. Completed the migration of the old
             test code in toolbox/test, moving the functionality to
             the new unit tests toolbox/xtest.

  0.9.14     Added SLIC superpixels. Added VL_ALPHANUM(). Improved
             Windows binary package and added support for Visual
             Studio 2010. Improved the documentation layout and added
             a proper bibliography. Bugfixes and other minor
             improvements. Moved from the GPL to the less restrictive
             BSD license.

  0.9.13     Fixes Windows binary package.

  0.9.12     Fixes vl_compile and the architecture string on Linux 32 bit.

  0.9.11     Fixes a compatibility problem on older Mac OS X versions.
             A few bugfixes are included too.

  0.9.10     Improves the homogeneous kernel map. Plenty of small tweaks
             and improvements. Make maci64 the default architecture on
             the Mac.

  0.9.9      Added: sift matching example. Extended Caltech-101
             classification example to use kd-trees.

  0.9.8      Added: image distance transform, PEGASOS, floating point
             K-means, homogeneous kernel maps, a Caltech-101
             classification example. Improved documentation.

  0.9.7      Changed the Mac OS X binary distribution to require
             a less recent version of Mac OS X (10.5).

  0.9.6      Changed the GNU/Linux binary distribution to require
             a less recent version of the C library.

  0.9.5      Added kd-tree and new SSE-accelerated vector/histogram
             comparison code.  Improved dense SIFT (dsift) implementation.
             Added Snow Leopard and MATLAB R2009b support.

  0.9.4      Added quick shift. Renamed dhog to dsift and improved
             implementation and documentation. Improved tutorials.
             Added 64 bit Windows binaries. Many other small changes.

  0.9.3      Namespace change (everything begins with a vl_ prefix
             now). Many other changes to provide compilation support
             on Windows with MATLAB 7.

  beta-3     Completions to the ikmeans code.

  beta-2     Many completions.

  beta-1     Initial public release.