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Hand-Gesture-Recognition
  • Classification:Numerical Algorithm-Artificial Intelligence - matlab
  • Development Tool:matlab
  • Sise:366 KB
  • Upload time:2011/5/27 21:57:29
  • Uploader:abhi
  • Download Statistics:
Description
Hand Gesture RecognitionNOTES:1) For the details of the algorithm investigate the following images:-AlgorithmOverall.jpg-MKRoDAlgorithm.jpg2) The prototype is implemented on MATLAB 7.0 and revised in MATLAB 7.10.03) The backgrounds of input images have to be purely ‘black’ and the details of the content(palms, fingers) must be clear for accurate recognition of the ASL.4) A reduced ASL dataset is used. The dataset contains the following ASL gestures: "b,c,h,i,o,l,y".----------------------------------------------------------------Use execHGR.m inside the Project folder in order to execute the program.I hope you will enjoy it.-Hand Gesture RecognitionNOTES:1) For the details of the algorithm investigate the following images:-AlgorithmOverall.jpg-MKRoDAlgorithm.jpg2) The prototype is implemented on MATLAB 7.0 and revised in MATLAB 7.10.03) The backgrounds of input images have to be purely ‘black’ and the details of the content(palms, fingers) must be clear for accurate recognition of the ASL.4) A reduced ASL dataset is used. The dataset contains the following ASL gestures: "b,c,h,i,o,l,y".----------------------------------------------------------------Use execHGR.m inside the Project folder in order to execute the program.I hope you will enjoy it.


y_sample.jpg

File list:
Hand Gesture Recognition
.......................\Project
.......................\.......\Images
.......................\.......\......\Database
.......................\.......\......\........\12.jpg
12.jpg
.......................\.......\......\........\15.jpg
15.jpg
.......................\.......\......\........\2.jpg
2.jpg
.......................\.......\......\........\25.jpg
25.jpg
.......................\.......\......\........\3.jpg
3.jpg
.......................\.......\......\........\8.jpg
8.jpg
.......................\.......\......\........\9.jpg
9.jpg
.......................\.......\......\Inputs
.......................\.......\......\......\sample
.......................\.......\......\......\......\a_caglar.jpg
a_caglar.jpg
.......................\.......\......\......\......\b_sample.jpg
b_sample.jpg
.......................\.......\......\......\......\b_sample_green.jpg
b_sample_green.jpg
.......................\.......\......\......\......\c_caglar.JPG
c_caglar.JPG
.......................\.......\......\......\......\c_sample.jpg
c_sample.jpg
.......................\.......\......\......\......\h_sample.jpg
h_sample.jpg
.......................\.......\......\......\......\i_sample.jpg
i_sample.jpg
.......................\.......\......\......\......\l_sample.jpg
l_sample.jpg
.......................\.......\......\......\......\o_sample.jpg
o_sample.jpg
.......................\.......\......\......\......\y_sample.jpg
y_sample.jpg
.......................\.......\appendimages.m
.......................\.......\execHGR.m
.......................\.......\findMax.m
.......................\.......\formResults.m
.......................\.......\hgr.m
.......................\.......\initDB.m
.......................\.......\isrgb1.m
.......................\.......\match.m
.......................\.......\sift.m
.......................\.......\siftWin32.exe
.......................\.......\theHGRDatabase.mat
.......................\Readme.txt
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