Head pose classification for passenger with CNN

被引：0
|
作者：
Biswas S. [1 ]
Chambers D. [2 ,4 ]
Hairston W.D. [3 ]
Bhattacharya S. [2 ,4 ]
机构：
[1] Data Science and Analytics, Kennesaw State University, 1100 South Marietta Pkwy SE, Marietta, 30060, GA
[2] Electrical Engineering Technology, Kennesaw State University, 1100 South Marietta Pkwy SE, Marietta, 30060, GA
[3] US DEVCOM Army Research Laboratory Aberdeen Proving Ground, MD
[4] Electrical Engineering Technology, Kennesaw State University, 1100 South Marietta PkwySE, Marietta, 30060, GA
来源：
Transportation Engineering | 2023年 / 11卷
关键词：
Autonomous driving technologies; Intelligence system; Machine learning techniques; Remotely sensed passenger head position;
D O I：
10.1016/j.treng.2022.100157
中图分类号：
学科分类号：
摘要：
The utilization of autonomous driving technologies has grown over the past few decades, but public perception has brought into question its effectiveness. With the potential to revolutionize traffic safety, its application is crucial. Apprehensiveness toward automated vehicles can be targeted by developing a reliable intelligence system tailored to the passenger's judgement of said system. The goal of this study is to examine passenger behavior in relation to the driver to develop applicable control structures that are able to react to responses from passengers. By employing machine learning techniques to identify the head position of passengers from video, this paper investigates a method for using remotely sensed passenger head position to understand the passengers' judgement of the driver. The results of this study reveal that passenger behavior can be assessed using remote head position sensing and their behavior can be used as a control structure in vehicles. We found that passengers kept their head straight majority of the drive which we consider as confirmation of the potential for future uses. © 2022
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