Gaze Classification on a Mobile Device by using Deep Belief Networks

被引：0
|
作者：
Park, Hyunsung [1 ]
Kim, Daijin [1 ]
机构：
[1] POSTECH, Pohang, South Korea
来源：
PROCEEDINGS 3RD IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION ACPR 2015 | 2015年
关键词：
TRACKING;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we introduce a gaze classification method which classifies the locations of human gaze on a display of a mobile device. For example, when the user see the upper part of a display, our method classifies the gaze as the upper part among the available choices: upper, middle, and lower parts of the display. Our method uses appearance-based gaze estimation and gray-scale images captured from a camera of a mobile device. This method does not require any personal calibration. We train gaze classifiers by using Deep Belief Networks with considering head poses in general environments for a mobile device. The gaze classification method is applied to human-computer interaction and various application programs.
引用
收藏
页码：685 / 689
页数：5
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