Fetching latest commit…
Cannot retrieve the latest commit at this time
|Failed to load latest commit information.|
VLFeat (Vision Library Features) Version 0.9.15 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/. 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 CHANGES 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.