Citation

Sonai Muthu Anbananthen, Kalaiarasi and Muhamad Amin, Anang Hudaya and Abdul Razak, Siti Fatimah and Abdullah, Mohd Fikri Azli and Yogarayan, Sumendra and Ibrahim, Siti Zainab and Mhlang, Imran Artwel Junior and Raman, Kirbana Jai (2019) Real Time Driver Anger Detection. In: Information Science and Applications 2018. Springer Verlag, Lecture Notes in Electrical Engineering, pp. 157-167. ISBN 978-981131055-3

Text 26.pdf - Published Version Restricted to Repository staff only Download (673kB)

Abstract

The field of artificial intelligence has seen an increasing number of researches being done related to facial expression recognition. Different methods have been proposed with some of them yielding good results and some performing poorly. Apart from that, anger plays a pivotal role in road accidents since road rage is stated to be one of the contributing factors to road accidents. In order to cater road rage and considering it being harmful to drivers and passengers, this paper proposes a real time driver anger detection. The project classifies human facial expressions, mainly anger expression in real time from a live video in order to warn the driver and eventually road accidents can be reduced.

Item Type:	Book Section
Uncontrolled Keywords:	Haar cascade classifier
Subjects:	Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	20 Sep 2021 03:48
Last Modified:	27 Apr 2023 13:34
URII:	http://shdl.mmu.edu.my/id/eprint/8982

Downloads

Edit (login required)