IJSEA Volume 11 Issue 12

A Method of Car Driver's Phone Call Recognition Based on Human Joint Points

Bowen Shi, Wenlong Wang, Xiaoyuan Wang
10.7753/IJSEA1112.1001
keywords : computer vision; deep learning; OpenPose; phone call recognition; biomechanical distraction

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The distracted driving state of the car driver has caused serious harm to traffic safety and the personal safety of the driver. The most frequent and common distraction is the distracted driving behavior of the driver on the phone. In order to accurately identify the car driver's phone call is distracting driving behavior. A driver's phone call behavior recognition method based on the joint point information of the driver's body was proposed in this manuscript. After using the OpenPose network structure to extract the joint points of the human body, the driver’s angle of the driver's upper and lower arms and the normalized distance between the joint points are calculated and compared to relatively accurate identification of car drivers' phone calls and distracted driving behaviors The experimental results show that the method proposed in this paper has an accuracy rate of 97.23% for the distracted driving state of the car driver's phone call.
@artical{b11122022ijsea11121001,
Title = "A Method of Car Driver's Phone Call Recognition Based on Human Joint Points ",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "11",
Issue ="12",
Pages ="250 - 253",
Year = "2022",
Authors ="Bowen Shi, Wenlong Wang, Xiaoyuan Wang"}