Real-time Yawning Detection Based on Machine Learning Algorithm and Time Series Classification using Facial Feature Points

被引：0

作者：

Chen, Kaihua ^{[1
]}

Zhu, Tingting ^{[1
]}

Li, Shaofeng ^{[1
]}

Shi, Yinxue ^{[1
]}

机构：

[1] China Agr Univ, Coll Informat & Elect Engn, Beijing, Peoples R China

来源：

2021 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE BIG DATA AND INTELLIGENT SYSTEMS (HPBD&IS) | 2021年

关键词：

yawning detection; LR plus BOSS; OpenPose; logistic regression; time series classification;

D O I：

10.1109/HPBDIS53214.2021.9658473

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Yawning detection is one of the facial action recognition problems, which has a wide range of applications. However, traditional approaches in relevant fields have many shortcomings. This paper first discusses how to utilize OpenPose to capture facial feature points, and then puts forward a new yawning detection method LR+BOSS by integrating machine learning algorithm logistics regression and time series classification algorithm BOSS, based on the YawDD dataset. In the experiments, we demonstrate that such a strategy makes obvious improvements compared with the traditional method and has huge potential to be applied in the real-time yawn detection system.

引用

页码：276 / 280

页数：5

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