Real-time Eye Detection in Video Streams

被引：4

作者：

Lin, Kunhui ^{[1
]}

Huang, Jiyong ^{[1
]}

Chen, Jiawei ^{[2
]}

Zhou, Changle ^{[2
]}

机构：

[1] Xiamen Univ, Software Sch, Xiamen 361005, Fujian, Peoples R China

[2] Xiamen Univ, Sch Informat Sci & Technol, Xiamen 361005, Peoples R China

来源：

ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 6, PROCEEDINGS | 2008年

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/ICNC.2008.278

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A fast eye detection scheme for use in video streams rather than still images is presented in this paper, The temporal coherence of sequential frames was used to greatly improve the detection speed. First, the eye defector trained by AdaBoost algorithm is used to obtain the rough eye positions. Then these candidate positions are filtered by geometrical patterns of human eyes. The detected eye regions are then taken as the initial detecting window. After each frame is detected, the detecting window is updated. The experiments focused on video stream to exploit the benefits of our defector. In our experiments the mean detection rate was 92.73% for 320x240 resolution test videos, with a speed of 24.98ms per frame. This speed is faster than previous research; however the detection rate does not dramatically decrease.

引用

页码：193 / +

页数：2

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