基于改进SVR的眼睛中心定位方法

doi:10.16451/j.cnki.issn1003-6059.201901003

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Abstract The accuracy of eye center localization is reduced due to the low resolution of input image, poor lighting condition, side face and eyes status. To handle this issue, an improved support vector regression (SVR) method is proposed to detect the eye center based on the facial feature localization. Several image processing techniques are tried to improve the accuracy. Results show that the SVR combining a Gaussian filter achieves a better accuracy.

Received: 23 September 2018

ZTFLH:

TP 29

Fund:Supported by National Natural Science Foundation of China(No.61733011,51575338)

Corresponding Authors: LIU Honghai, Ph.D., professor. His research interests include biomechatronics, pattern recognition, intelligent video analytics and intelligent robotics.

About author:: ZHANG Wanqi, master student. Her research interests include human-machine inte-lligent system, skeleton extraction and action segmentation.WANG Zhiyong, Ph.D candidate. His research interests include image processing, facial feature points detection and gaze estimation.)

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Cite this article:

ZHANG Wanqi,WANG Zhiyong,LIU Honghai. Eye Center Localization Based on Improved SVR[J]. , 2019, 32(1): 17-23.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201901003 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I1/17

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