HogPSVM-Pedestrian-Detection-

所属分类:matlab编程
开发工具:matlab
文件大小:9406KB
下载次数:340
上传日期:2016-03-13 12:35:14
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说明:  保证可用的,希望好评!!!HOG+SVM进行图片中行人检测,提供训练用的pos和neg样本,效果还可以(也是本网站下载代码,但是原始的作者故意改错一些地方,我已经一一修正,完全可以运行;没有SVM工具箱的,压缩包里已经提供了,安装一下即可)
(HOG+SVM pedestrian detection)

文件列表:
可以用的行人检测\alpha.mat (1758, 2016-03-10)
可以用的行人检测\bias.mat (173, 2016-03-10)
可以用的行人检测\HOG.m (9572, 2011-05-11)
可以用的行人检测\imhogtrace.m (3849, 2016-03-13)
可以用的行人检测\myplot.m (289, 2016-03-10)
可以用的行人检测\narrowarray.mat (210, 2016-03-13)
可以用的行人检测\neg\img00007.jpg (3742, 2013-12-04)
可以用的行人检测\neg\img00036.jpg (12381, 2013-12-04)
可以用的行人检测\neg\img00041.jpg (17678, 2013-12-04)
可以用的行人检测\neg\img00119.jpg (21730, 2013-12-04)
可以用的行人检测\neg\img00120.jpg (9943, 2013-12-04)
可以用的行人检测\neg\img00170.jpg (4527, 2013-12-04)
可以用的行人检测\neg\img00257.jpg (2558, 2013-12-04)
可以用的行人检测\neg\img00341.jpg (3982, 2013-12-04)
可以用的行人检测\neg\img00562.jpg (3770, 2013-12-04)
可以用的行人检测\neg\img00818.jpg (6241, 2013-12-04)
可以用的行人检测\neg\img00897.jpg (1575, 2013-12-04)
可以用的行人检测\neg\img01003.jpg (3847, 2013-12-04)
可以用的行人检测\neg\img01059.jpg (3204, 2013-12-04)
可以用的行人检测\neg\img01065.jpg (4183, 2013-12-04)
可以用的行人检测\neg\img01144.jpg (4671, 2013-12-04)
可以用的行人检测\neg\img01207.jpg (9216, 2013-12-04)
可以用的行人检测\neg\img01259.jpg (3453, 2013-12-04)
可以用的行人检测\neg\img01260.jpg (15921, 2013-12-04)
可以用的行人检测\neg\img01305.jpg (14936, 2013-12-04)
可以用的行人检测\neg\img01360.jpg (5556, 2013-12-04)
可以用的行人检测\neg\img01381.jpg (3963, 2013-12-04)
可以用的行人检测\neg\img01460.jpg (5440, 2013-12-04)
可以用的行人检测\neg\img01480.jpg (2115, 2013-12-04)
可以用的行人检测\neg\img01523.jpg (4501, 2013-12-04)
可以用的行人检测\neg\img01524.jpg (3696, 2013-12-04)
可以用的行人检测\neg\img01591.jpg (7004, 2013-12-04)
可以用的行人检测\neg\img01641.jpg (4424, 2013-12-04)
可以用的行人检测\neg\img01724.jpg (6955, 2013-12-04)
可以用的行人检测\neg\img01790.jpg (5923, 2013-12-04)
可以用的行人检测\neg\img01797.jpg (3086, 2013-12-04)
可以用的行人检测\neg\img01813.jpg (15912, 2013-12-04)
可以用的行人检测\neg\img01915.jpg (6087, 2013-12-04)
可以用的行人检测\neg\img02000.jpg (4701, 2013-12-04)
可以用的行人检测\neg\img02024.jpg (5431, 2013-12-04)
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Matlab Support Vector Machine Toolbox ------------------------------------- Author: Steve Gunn This toolbox was designed as a teaching aid, which matlab is particularly good for since source code is relatively legible and simple to modify. However, it is still reasonably fast if used with the supplied optimiser. However, if you really want to speed things up you should consider compiling the matrix composition routine for H into a mex function. Then again if you really want to speed things up you probably shouldn't be using matlab anyway... Get hold of a dedicated C program once you understand the algorithm. Enjoy! Version Info ------------ Version: 2.1, 12/10/2001 - interior point QP optimiser added Version: 2.0, 01/08/19*** - Bug Fixes Version: 1.0, 10/02/19*** - Initial release Licence ------- The Support Vector Machine Toolbox is ONLY available for academic purposes. It is not available for industrial or commercial applications of any kind without explicit arrangement with the author. The software must not be posted on any WWW or ftp sites or distributed in any other way without prior permission of the author. The author disclaims all warranties with regard to this software, including all implied warranties of merchantability and fitness. In no event shall the authors be liable for any special, indirect or consequential damages or any damages whatsoever resulting from loss of use, data or profits, whether in an action of contract, negligence or other tortious action, arising out of or in connection with the use or performance of this software. Permission to sell this software is not granted. Installation ------------ The distribution now comes in a zip file (partly due to some problems people were having trying to open tar files with winzip). Unzip the toolbox under the matlab toolbox directory and add ......./matlab/toolbox/svm to the matlab path. If you are running under a windows OS you should be ready to go. On an alternative OS you will need to build the optimiser. NOTE: The matlab optimisation toolbox also currently contains a qp program, although it says that it will be replaced by a quadprog in the future. Make sure that the svm toolbox path comes before at the front of the matlab path, and it will then use the routine supplied with the svm toolbox which should be more efficient. Optimiser --------- Go into the optimiser directory and type, mex -v qp.c pr_loqo.c mv qp.mex??? .. which will build the optimiser for your OS, where the extension .mex??? will vary depending upon your OS. Move this file up one directory or add the optimiser directory to the path as well

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