Driver Fatigue Detection Based on Face Mesh Features Using Deep Learning

Imam Nuralif, Eko Mulyanto Yuniarno, Yoyon Kusnendar Suprapto, Alif Aditya Wicaksono

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The number vehicles and road users increases every year, this also has the potential to increase the risk of traffic accidents. Fatigue is the most dominant cause of accidents compared to several other factors. This research focuses on detecting driver fatigue. We use the mediapipe face mesh model to extract the key points on the face, next is to utilize the deep learning model, Long Short Term Memory (LSTM), which has been trained previously and implemented into mediapipe to detect driver fatigue. The data that is trained is the data point movement of facial features, so that the system can not only process one frame but several frames. The data given by the camera will be processed using the LSTM model's ability to detect long-term information, dynamically process data, and handle picture data using mediapipe in order to achieve low computational and high accuracy. The LSTM model has better accuracy in predicting facial features than the conventional random forest model.

Original languageEnglish
Title of host publication2023 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationLeveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9798350313956
DOIs
Publication statusPublished - 2023
Event24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023 - Hybrid, Surabaya, Indonesia
Duration: 26 Jul 202327 Jul 2023

Publication series

Name2023 International Seminar on Intelligent Technology and Its Applications: Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding

Conference

Conference24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023
Country/TerritoryIndonesia
CityHybrid, Surabaya
Period26/07/2327/07/23

Keywords

  • Deep Learning
  • Face Mesh
  • Fatigue detection
  • Mediapipe

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