shapecontext6

所属分类:图形图像处理
开发工具:matlab
文件大小:1068KB
下载次数:262
上传日期:2011-07-11 13:46:54
上 传 者fearwang
说明:  形状上下文算法用于图像检索,程序中已运用了.mat文件存储图像库中的图像特征,检索效果很好。
(shapecontext is used to realize imgage retrival,it shows very effective performance.)

文件列表:
shapecontext6\bdry_extract_3.m (634, 2000-09-04)
shapecontext6\bookstein.m (659, 2000-09-04)
shapecontext6\C.mat (690363, 2011-07-11)
shapecontext6\CC.mat (2847, 2011-07-11)
shapecontext6\demo.asv (3944, 2011-07-08)
shapecontext6\demo.m (3944, 2011-07-08)
shapecontext6\dist2.m (820, 2000-09-04)
shapecontext6\gaussker.m (115, 2000-09-04)
shapecontext6\get_samples_1.m (577, 2009-11-29)
shapecontext6\hist_cost_2.m (432, 2000-09-04)
shapecontext6\hungarian.m (11250, 2000-09-04)
shapecontext6\im.m (335, 2000-09-04)
shapecontext6\main_box.m (96, 2008-03-21)
shapecontext6\main_shapecontext.m (1153, 2008-03-21)
shapecontext6\sc_compute.m (1963, 2000-09-05)
shapecontext6\shapcontext_main.m (2232, 2011-07-08)
shapecontext6\T2.mat (34879, 2011-07-11)
shapecontext6\T3.mat (142927, 2011-07-11)
shapecontext6\T4.mat (275654, 2011-07-11)
shapecontext6\tps_iter_match_1.m (4866, 2008-03-20)
shapecontext6\train.asv (1343, 2010-03-15)
shapecontext6\train.m (1343, 2010-03-15)
shapecontext6 (0, 2011-07-08)

Shape Context Demo Serge Belongie (sjb@eecs.berkeley.edu) Sept. 4, 2000 1. Information on Chui and Rangarajan data (for demo_1.m) Each filename is of the form save_{fish,chinese,hand}_{def,noise,outlier}_m_n.mat The value of m refers to the test number, n refers to the test example number. The range of m is 1-5 for deformation and outlier, 1-6 for noise. The range of n is 1-100. Example: save_fish_outlier_3_2.mat This corresponds to the "fish" shape, outlier test, test no. 3 (out of 5), corresponding to 100% outlier to data ratio, example no. 2. Each file contains the model data (x1), the target data (y2a), and in the case of the noise test, the target data before adding noise (y2). 2. Information on Digit Matching test (for demo_2.m) This uses test data from Yann LeCun's MNIST database; see http://www.research.att.com/~yann/ocr/mnist/ for details.

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