Driver cellphone usage detection using wavelet scattering and convolutional neural networks

نویسندگان

1 Virtual Reality Laboratory, K.N. Toosi University of Technology, Tehran, Iran

2 Virtual Reality Laboratory, K.N. Toosi University of Technology, Tehran, Iran

3 Virtual Reality Laboratory, K.N. Toosi University of Technology, Tehran, Iran

doi
10.22060/ajmc.2023.22580.1177
چکیده

This paper provides an automated system based on machine learning and computer vision to detect cellphone usage during driving. We used Wavelet Scattering Networks, which is a simple and efficient type of architecture. The pre[1]sented model is straightforward and compact and requires little hyper-parameter tuning. The speed of this model is similar to the Convolutional Neural Networks. We monitored the driver from two viewpoints: a frontal view of the driver’s face and a side view of the driver’s whole body. We created a new dataset for the first view[1]point, and used a publicly available dataset for the second viewpoint. Our model achieved the test accuracy of 91% for our new dataset and 99% for the publicly available one.