Gazing-detection of human eyes based on SVM

Gazing-detection of human eyes based on SVM

A method for gazing-detection of human eyes using Support Vector Machine （SVM） based on statistic leaming theory （SLT） is proposed. According to the criteria of structural risk minimization of SVM,the errors between sample-data and model-data are minimized and the upper bound of predicting error of...

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Veröffentlicht in:光电子快报：英文版 2005, Vol.1 (1), p.65-68
1. Verfasser: LI Su-mei ZHANG Yan-xin CHANG Sheng-jiang SHEN Jin-yuan
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Sprache:eng
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凝视检测
向量支持装置
识别系统
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creator LI Su-mei ZHANG Yan-xin CHANG Sheng-jiang SHEN Jin-yuan
description A method for gazing-detection of human eyes using Support Vector Machine （SVM） based on statistic leaming theory （SLT） is proposed. According to the criteria of structural risk minimization of SVM,the errors between sample-data and model-data are minimized and the upper bound of predicting error of the model is also reduced. As a result,the generalization ability of the model is much improved. The simulation results show that, when limited training samples are used, the correct recognition rate of the tested samples can be as high as 100% ,which is much better than some previous results obtained by other methods. The higher processing speed enables the system to distinguish gazing or not-gazing in real-time.
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subjects 凝视检测
向量支持装置
识别系统
title Gazing-detection of human eyes based on SVM
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