Mobile device based eye tracking technology

被引：1

作者：

Cheng S.-W. ^{[1
]}

Lu Y.-H. ^{[1
]}

Cai H.-G. ^{[1
]}

机构：

[1] School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou

来源：

Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2016年 / 50卷 / 06期

关键词：

Eye tracking; Human-computer interaction; Pupil detection; Reading assistance;

D O I：

10.3785/j.issn.1008-973X.2016.06.021

中图分类号：

学科分类号：

摘要：

A hierarchical processing framework and the related detect approaches were proposed, treating images from face to pupil areas in order to develop high efficient and accurate eye tracking technique on mobile device. Firstly, local binary pattern based cascaded classifier was applied to classify face and non-face areas of the image. Then Haar feature based cascaded classifier was used to detect eye areas, and image template-matching method was applied to detect pupil position within eye areas. Finally, an eye tracking reading assistant system was developed, which could detect the change of pupil position and locate the text line where users currently read. The system could help users find the text line to continue reading when they were interrupted. The results of users' test show that the system has eye tracking accuracy at 1.17° of visual angle in average, and can locate the text lines accurately. The system can help users achieve the average reading speed at 12.42 words per second. The effectiveness of the eye tracking technique was verified. © 2016, Zhejiang University Press. All right reserved.

引用

页码：1160 / 1166and1175

共 21 条

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