Home / Current Issue / Paper 1704928
YOLO based approach for Helmet and Seatbelt Detection
Subject area: Science,Engineering and Technology · Area of research: Machine Learning
Abstract
Increase in the number of transportation vehicles has led to heavy traffic loads and thus many transportation routes are created. Due to this people might lose patience which may lead to many accidents and traffic injuries. Hence rules are enforced upon people to wear helmets while riding bikes and seat belts while driving cars to minimize the chances on casualty in case of accidents. Many people do not follow the traffic rules and get involved in traffic rule violation. Since the monitoring of those rules are done manually by traffic police things might get difficult for the police to monitor each and every vehicle. Hence, a model has been proposed to detect whether helmet or seat belt is worn using the machine learning technique. In this paper, a survey has been done and found that helmet detection model could be built with the help of Convolutional Neural Network (CNN) and You Only Look Once (YOLO)v3. YOLOv2 can also be used which has to be trained with COCO datasets. For seat belt detection YOLOv5 method is used along with the combination of CNN and Support Vector Machine (SVM) models. The proposed model decreases the burden on traffic police and also helps in achieving efficiency.
Keywords
Helmet, Seat belt, YOLOv2, YOLOv3, YOLOv5, Convolutional Neural Network, SVM
References
[1] Fahad A Khan, Nitin Nagori, Dr. Ameya Naik, Helmet and Number Plate Detection of Motorcyclists using Deep Learning and Advanced Machine Vision Techniques, ICIRCA, IEEE, 2020.
[2] S Sanjana, V R Shriya, Gururaj, Vaishnavi, K Ashwini, A review on various methodologies used for vehicle classification, helmet detection and number plate recognition, Evolutionary Intelligence, Springer, 2020.
[3] Meghal Darji, Jaivik Dave, Nadim Asif, Chirag Godawat, Vishal Chudasama, Kishor Upla, License plate Identification and Recognition for non-Helmeted Motorcyclists using Light-Weight Convolutional Neural Network, International Conference for Emerging Technology (INCET), IEEE, 2020.
[4] C. Vishnu, Dinesh Singh, C. Krishna Mohan, Sohan Babu, Detection of Motorcyclists without Helmet in Videos using Convolutional Neural Network, Visual Intelligence and Learning Group (VIGIL), Indian Institute of Technology Hyderabad, IEEE, 2017.
[5] Madhuchhanda Dasgupta, Oishila Bandyopadh- yay, Sanjay Chatterji, Automated Helmet Detection for Multiple Motorcycle Riders using CNN, Conference on Information and Communication Technology (CICIT), IEEE, 2019.
[6] Shashidhar R, A S Manjunath, Santosh Kumar R, Roopa M, Puneeth S B, Vehicle Number Plate Detection and Recognition using YOLOv3 and OCR Method, IEEE, 2021.
How to cite this paper
@article{1704928,
author = {Sudeep Manohar, Preethi B V, Preethi T, Sameeksha B, Sharvani S},
title = {YOLO based approach for Helmet and Seatbelt Detection},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {7},
number = {2},
pages = {66-71},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1704928.pdf},
abstract = {Increase in the number of transportation vehicles has led to heavy traffic loads and thus many transportation routes are created. Due to this people might lose patience which may lead to many accidents and traffic injuries. Hence rules are enforced upon people to wear helmets while riding bikes and seat belts while driving cars to minimize the chances on casualty in case of accidents. Many people do not follow the traffic rules and get involved in traffic rule violation. Since the monitoring of those rules are done manually by traffic police things might get difficult for the police to monitor each and every vehicle. Hence, a model has been proposed to detect whether helmet or seat belt is worn using the machine learning technique. In this paper, a survey has been done and found that helmet detection model could be built with the help of Convolutional Neural Network (CNN) and You Only Look Once (YOLO)v3. YOLOv2 can also be used which has to be trained with COCO datasets. For seat belt detection YOLOv5 method is used along with the combination of CNN and Support Vector Machine (SVM) models. The proposed model decreases the burden on traffic police and also helps in achieving efficiency.},
keywords = {Helmet, Seat belt, YOLOv2, YOLOv3, YOLOv5, Convolutional Neural Network, SVM},
month = {August},
}