vlfeat-0.9.18-bin
所属分类:matlab编程
开发工具:matlab
文件大小:16749KB
下载次数:56
上传日期:2014-04-09 10:49:13
上 传 者:
xiaowei19870119
说明: 行人检测、图像目标分类的相关特征如HOG,SIFT、LIOP、聚类等,对初始研究者有很大帮助。
(Pedestrian detection, correlation feature of image classification as HOG, SIFT, LIOP, clustering, the initial investigators of great help.)
文件列表:
vlfeat-0.9.18-bin (0, 2014-04-08)
vlfeat-0.9.18-bin\pax_global_header (52, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18 (0, 2014-04-08)
vlfeat-0.9.18-bin\vlfeat-0.9.18\COPYING (1365, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\Makefile (11433, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\Makefile.mak (17536, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps (0, 2014-04-08)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\phow_caltech101.m (11594, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition (0, 2014-04-08)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\encodeImage.m (5278, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\experiments.m (6905, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\extendDescriptorsWithGeometry.m (822, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\getDenseSIFT.m (1679, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\readImage.m (919, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\setupCaltech256.m (2495, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\setupFMD.m (1197, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\setupGeneric.m (4024, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\setupScene67.m (2368, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\setupVoc.m (5189, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\trainEncoder.m (6226, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\recognition\traintest.m (6097, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\apps\sift_mosaic.m (4621, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin (0, 2014-04-08)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86 (0, 2014-04-08)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\aib (8396, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\libvl.so (293498, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\mser (21717, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\sift (26345, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_gauss_elimination (8327, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_getopt_long (8597, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_gmm (13455, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_heap-def (12462, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_host (8345, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_imopv (8611, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_kmeans (8500, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_liop (8389, 2014-01-31)
vlfeat-0.9.18-bin\vlfeat-0.9.18\bin\glnx86\test_mathop (12490, 2014-01-31)
... ...
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
> MKOCTFILE= 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 maci*** 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 *** 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.
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