Abstract
One of the major causes of road accidents is driver distraction. Driver distraction is diversion of attention away from activities critical for safe driving. Driver distraction can be categorized into drowsiness and inattentiveness. Drowsiness is a condition in which the driver feels sleepy, therefore cannot pay attention toward road. Inattentiveness is diversion of driver’s attention away from the road. Our system provides facility for monitoring driver’s activities continuously. The in-car camera is mounted to capture live video of driver. Viola–Jones algorithm is used to identify the driver’s non-front-facing frames from video. Inattentiveness is detected if the system identifies consecutive frames having non-frontal face. Drowsiness is identified by continuous monitoring of the eye status, which is either “open” or “closed” using horizontal mean intensity plot of eye region. Once the system detects the distraction, alert is generated in the form of audio. This will reduce the risk of falling asleep in long distance traveling during day and night time.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Panicker, A.D., Nair, M.S.: Open-eye detection using iris–sclera pattern analysis for driver drowsiness detection. Sadhana 42(11), 1835–1849 (2017)
Maralappanavar, S., Behera, R.K., Mudenagudi, U.: Driver’s distraction detection based on gaze estimation. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, pp. 2489–2494 (2016)
Yan, J.-J., Kuo, H.-H., Lin, Y.-F., Liao, T.-L.: Real-time driver drowsiness detection system based on PERCLOS and grayscale image processing. In: International Symposium on Computer, Consumer and Control, Xi’an, China, pp. 243–246 (2016)
Kong, W., Zhou, L., Wang, Y., Zhang, J., Liu, J., Ga, S.: A system of driving fatigue detection based on machine vision and its application on smart device. J. Sens. (2015)
Moreno, R.J., Sánchez, O.A., Hurtado, D.A.: Driver distraction detection using machine vision techniques. Ingeniería y Competitividad 16(2), 55–63 (2014)
Eren, H., Makinist, S., Akin, E., Yilmaz, A.: Estimating driver behavior by a smartphone. In: IEEE Intelligent Vehicles Symposium Alcalá de Henares, Spain, pp. 234–239 (2012)
Batista, J.: A drowsiness and point of attention monitoring system for driver vigilance. In: IEEE Intelligent Transportation Systems Conference, USA, pp. 702–708 (2007)
Viola, P., Jones, M.: Robust real-time face detection. Kluwer Int. J. Comput. Vis. 57(2), 137–154 (2004)
AT & T Laboratories Cambridge. http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html
Acknowledgements
The authors express their deep sense of gratitude and indebtedness to Dr. Amol R. Madane (TCS) who was very kind to provide us with an opportunity to work under his immense expertise. His prompt inspiration, suggestions with kindness and dynamism enabled us to shape the present work as it shows. We would like to express our sincere gratitude toward our project guide Dr. A. M. Deshpande for her constant encouragement and valuable guidance.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Modak, A., Paradkar, S., Manwatkar, S., Madane, A.R., Deshpande, A.M. (2020). Human Head Pose and Eye State Based Driver Distraction Monitoring System. In: Chaudhuri, B., Nakagawa, M., Khanna, P., Kumar, S. (eds) Proceedings of 3rd International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1022. Springer, Singapore. https://doi.org/10.1007/978-981-32-9088-4_34
Download citation
DOI: https://doi.org/10.1007/978-981-32-9088-4_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-32-9087-7
Online ISBN: 978-981-32-9088-4
eBook Packages: EngineeringEngineering (R0)