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Head motion coefficient-based algorithm for distracted driving detection

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成果类型:
期刊论文
作者:
Chui, Kwok Tai*;Alhalabi, Wadee;Liu, Ryan Wen
通讯作者:
Chui, Kwok Tai
作者机构:
[Chui, Kwok Tai] City Univ Hong Kong, Coll Sci & Engn, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China.
[Alhalabi, Wadee] King Abdulaziz Univ, Dept Comp Sci, Jeddah, Saudi Arabia.
[Alhalabi, Wadee] Effat Univ, Virtual Real Res Ctr, Jeddah, Saudi Arabia.
[Liu, Ryan Wen] Wuhan Univ Technol, Sch Nav, Wuhan, Hubei, Peoples R China.
通讯机构:
[Chui, Kwok Tai] C
City Univ Hong Kong, Coll Sci & Engn, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China.
语种:
英文
关键词:
Correlation analysis;Public transport;Social good;Road safety;Distracted driving;Head motion
期刊:
DATA TECHNOLOGIES AND APPLICATIONS
ISSN:
2514-9288
年:
2019
卷:
53
期:
2
页码:
171-188
机构署名:
本校为其他机构
院系归属:
航运学院
摘要:
Purpose: Concentration is the key to safer driving. Ideally, drivers should focus mainly on front views and side mirrors. Typical distractions are eating, drinking, cell phone use, using and searching things in car as well as looking at something outside the car. In this paper, distracted driving detection algorithm is targeting on nine scenarios nodding, head shaking, moving the head 45° to upper left and back to position, moving the head 45° to lower left and back to position, moving the head 45° to upper right and back to position, moving...

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