Gabor_Face_Recogntion
所属分类：模式识别(视觉/语音等)
开发工具：matlab
文件大小：211KB
下载次数：35
上传日期：2010-12-02 13:24:24
上 传 者：
dyingfair
说明： 利用Gabor特征进行人脸识别的论文与matlab实现算法，比较新，感觉还不错。
(Face recognition using Gabor features papers and matlab algorithm, a relatively new, I feel pretty good.)
文件列表:
Gabor Face Recogntion\Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary.pdf (248765, 2010-12-01)
Gabor Face Recogntion\GSRC_ECCV\main_gsrc.m (3838, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\main_gsrc_occlusion.m (3199, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\main_gsrc_occlusion_partition.m (5535, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\main_learn_occlusion_dict.m (2637, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\Create_GaborF.asv (2541, 2010-07-09)
Gabor Face Recogntion\GSRC_ECCV\utilities\Create_GaborF.m (2900, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\Eigenface_f.m (1569, 2010-07-09)
Gabor Face Recogntion\GSRC_ECCV\utilities\Gabor_T_Fast1.m (745, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\MakeAllGaborKernal.m (782, 2010-07-09)
Gabor Face Recogntion\GSRC_ECCV\utilities\MakeGaborKernal.m (1037, 2010-07-08)
Gabor Face Recogntion\GSRC_ECCV\utilities\Metaface_single_iteration.asv (1148, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\Metaface_single_iteration.m (1253, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\Occlusion_Dict_Learn.asv (425, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\Occlusion_Dict_Learn.m (497, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities\setpara_occlu.m (1085, 2010-07-10)
Gabor Face Recogntion\GSRC_ECCV\utilities (0, 2010-12-02)
Gabor Face Recogntion\GSRC_ECCV (0, 2010-12-02)
Gabor Face Recogntion (0, 2010-12-02)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
This code is for the paper
M. Yang and L. Zhang. Gabor feature based sparse representation for face recognition with Gabor occlusion dictionary.
In ECCV 2010.
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Note:
1. Please prepare the three face databases (Extended YaleB, AR and FERET pose subset) by yourself.
2. Download the l1_ls toolbox (http://stanford.edu/~boyd/l1_ls/), and add the path of l1_ls toolbox to matlab.
3. Follow the instruction of the main functions to do the experiment.
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