• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Feature Based Techniques for a Driver's Distraction Detection using Supervised Learning Algorithms based on Fixed Monocular Video Camera

Vol. 12, No. 8, August 30, 2018
10.3837/tiis.2018.08.015 , Download Paper (Free):

Abstract

Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver’s head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver’s distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver’s distraction, i.e., driver’s head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver’s head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.


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Cite this article

[IEEE Style]
S. F. Ali and M. T. Hassan, "Feature Based Techniques for a Driver's Distraction Detection using Supervised Learning Algorithms based on Fixed Monocular Video Camera," KSII Transactions on Internet and Information Systems, vol. 12, no. 8, pp. 3820-3841, 2018. DOI: 10.3837/tiis.2018.08.015 .

[ACM Style]
Syed Farooq Ali and Malik Tahir Hassan. 2018. Feature Based Techniques for a Driver's Distraction Detection using Supervised Learning Algorithms based on Fixed Monocular Video Camera. KSII Transactions on Internet and Information Systems, 12, 8, (2018), 3820-3841. DOI: 10.3837/tiis.2018.08.015 .