The Application of Support Vector Machines in The Automatic Eye Position Algorithm

摘要：

Support Vector Machine (SVM) was a new and outstanding machine learning as an efficient machine learning tool in dealing with small samples.In this paper,an new automatic eye position algorithm based on SVM is introduced, which is fast and accurate and the eyeballs center position velocity is only 1 second. The position accuracy is up to 95 percent and average position error is about 3 pi1xeis. Comparez to existing eye Iocaliztion algorithm, the algorithm mentioned in this paper is simple and easy to implement for position. The experimental results show that this new method is satisfying in accuracy of the automatic eye position, and using this algorithm, the position velocity is faster and position accuracy is higher than other eye position algorithm.

关键词： SVM eye position machine learning

作者: Wang Xueguang Du Xiaowei

作者单位: College of Information and Electrical Engineering,Hebei University of Engineering Handan,Hebei province

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 485-488

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）