Presentation | 2010-03-16 Hand Shape Recognition based on SVM and online learning with HOG Ryousuke MUTOU, Kazutaka SIMADA, Tutomu ENDOU, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper, we proposed a combined method for hand shape recognition. It consists of support vector machines (SVMs) and an online learning algorithm based on the percepron. We apply HOG features to each method. First, our method estimates a hand shape of an input image by using SVMs. Also the online learning method with the perceptron uses the input image as training data if the data possesses a high confidence score in the recognition process. Next, we select the final hand shape from the outputs from the SVMs and perceptron by using the score from SVMs. We compared the combined method with SVMs. The experimental results show the effectiveness of the proposed method. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | hand shape recognition / online learning / HOG |
Paper # | PRMU2009-311,HIP2009-196 |
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Committee | PRMU |
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Conference Date | 2010/3/8(1days) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Hand Shape Recognition based on SVM and online learning with HOG |
Sub Title (in English) | |
Keyword(1) | hand shape recognition |
Keyword(2) | online learning |
Keyword(3) | HOG |
1st Author's Name | Ryousuke MUTOU |
1st Author's Affiliation | Kyushu Institute of Technology Computer Science and Systems Engineering() |
2nd Author's Name | Kazutaka SIMADA |
2nd Author's Affiliation | Kyushu Institute of Technology Computer Science and Systems Engineering |
3rd Author's Name | Tutomu ENDOU |
3rd Author's Affiliation | Kyushu Institute of Technology Computer Science and Systems Engineering |
Date | 2010-03-16 |
Paper # | PRMU2009-311,HIP2009-196 |
Volume (vol) | vol.109 |
Number (no) | 470 |
Page | pp.pp.- |
#Pages | 6 |
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