BOW-MATLAB
所属分类：图形图像处理
开发工具：matlab
文件大小：3425KB
下载次数：22
上传日期：2015-05-12 17:06:31
上 传 者：
hmyhmyhmy123
说明： BOW主要是对图像的金字塔进行分块描述，进一步生成模型或者判别模型完成图像分类。在图像搜索和筛选中发挥着重要作用
(BOW mainly on image pyramids block description, further models or discriminant model generates complete image classification. It plays an important role in image search and screening)
文件列表:
BOW (0, 2015-01-07)
BOW\CalculateDictionary.m (3709, 2015-01-07)
BOW\CompilePyramid.m (3260, 2015-01-07)
BOW\EuclideanDistance.m (1303, 2015-01-07)
BOW\GenerateSiftDescriptors.m (2690, 2015-01-07)
BOW\MakeDataDirectory.m (569, 2015-01-07)
BOW\do_assignment.m (2384, 2015-01-07)
BOW\do_classification_inter_svm.m (1882, 2015-01-07)
BOW\do_classification_rbf_svm.m (1416, 2015-01-07)
BOW\do_normalize.m (875, 2015-01-07)
BOW\do_p_classification_inter_svm.m (2307, 2015-01-07)
BOW\do_p_classification_rbf_svm.m (1385, 2015-01-07)
BOW\draw_cm.m (1258, 2015-01-07)
BOW\find_grid.m (436, 2015-01-07)
BOW\find_sift_grid.m (4155, 2015-01-07)
BOW\hist_isect.m (729, 2015-01-07)
BOW\hist_isect_c.c (3119, 2015-01-07)
BOW\load_image.m (146, 2015-01-07)
BOW\make_dir.m (213, 2015-01-07)
BOW\normalize_sift.m (632, 2015-01-07)
BOW\num2string.m (309, 2015-01-07)
BOW\read_image_db.m (253, 2015-01-07)
BOW\rotateXLabels.m (13971, 2015-01-07)
BOW\show_results_script.m (551, 2015-01-07)
BOW\sumnormalize.m (236, 2015-01-07)
LBP (0, 2015-01-07)
LBP\getmapping.m (2662, 2015-01-07)
LBP\lbp.m (5835, 2015-01-07)
images (0, 2015-01-07)
images\testing (0, 2015-01-07)
images\testing\Phoning (0, 2015-01-07)
images\testing\Phoning\Phoning_0041.jpg (7711, 2015-01-07)
images\testing\Phoning\Phoning_0042.jpg (5900, 2015-01-07)
images\testing\Phoning\Phoning_0043.jpg (7294, 2015-01-07)
images\testing\Phoning\Phoning_0044.jpg (5867, 2015-01-07)
images\testing\Phoning\Phoning_0045.jpg (8424, 2015-01-07)
images\testing\Phoning\Phoning_0046.jpg (8039, 2015-01-07)
... ...
========================================================================
Image Classification using Bag of Words and Spatial Pyramid BoW
Created by Piji Li
Email: pagelee.sd@gmail.com
Blog: http://www.zhizhihu.com
Weibo: http://www.weibo.com/pagecn
10/24/2011
Some code are from:
S. Lazebnik, C. Schmid, and J. Ponce, "Beyond Bags of Features: Spatial
Pyramid Matching for Recognizing Natural Scene Categories," CVPR 2006.
========================================================================
Use:
1, follow labes/readme to prepare data
2, go to libsvm/: make
3, modify ini.m: rootpath=your demo path, and then run main.m.
The BOW and Dictionary is in the dir:/data/global, size of BOW_sift.mat is (DictionarySize * #images).
Size of dictionary.mat is (DictionarySize * dim of features).spatial_pyramid.mat is the Spatial Pyramid BoW.
In /data/local is the sift features for each images.
========================================================================
Classification using BOW rbf_svm
Accuracy = 76.6667% (92/120) (classification)
Classification using histogram intersection kernel svm
Accuracy = 81.6667% (***/120) (classification)
Classification using Pyramid BOW rbf_svm
Accuracy = 82.5% (99/120) (classification)
Classification using Pyramid BOW histogram intersection kernel svm
Accuracy = 90% (108/120) (classification)
========================================================================
Idea from:
S. Lazebnik, C. Schmid, and J. Ponce, "Beyond Bags of Features: Spatial
Pyramid Matching for Recognizing Natural Scene Categories," CVPR 2006.
Images from:
Piji Li, Jun Ma, Shuai Gao. Actions in Still Web Images: Visualization, Detection and Retrieval.
The 12th International Conference on Web-Age InformationManagement (WAIM 2011). Springer, 2011.
SVM from:
Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines.
ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
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