Any kind of vehicle driving is one of the most challenging tasks in this world requiring simultaneous
accomplishment of numerous sensory, cognitive, physical and psychomotor skills. There are various
number of factors are involved in automobile crash such as driver skill, behaviour and impairment due to
drugs, road design, vehicle design, speed of operation, road environment, notably speeding and street
racing. This study focuses a vision based framework to monitor driver’s attention level in real time by using
Microsoft Kinect for Windows sensor V2. Additionally, the framework generates an awareness signal to the
driver in case of low attention. The effectiveness of the system demonstrates through board experiments in
case of hostile light conditions also. Experimental result illustrates the quite well functionality of the
framework with 11 participants and measures the attention level of participants with equitable precision.
%0 Journal Article
%1 noauthororeditor
%A Lata, Munira Akter
%A Rahman, Md Mahmudur
%A Yousuf, Mohammad Abu
%A Ananya, Md. Ibrahim Al
%A Roy, Devzani
%A Mahadi, Alvi
%D 2018
%J International Journal of Computer Science, Engineering and Information Technology(IJCSEIT)
%K (AE) (AF) (AM) (ES) (FA) (MM) (SDK) Angle Attention Development Eye Face Kinect Kit Motion Mouth Software State and with
%N 1
%P 13-26
%R 10.5121/ijcseit.2018.8102
%T DEVELOPMENT OF AN EMPIRICAL MODEL TO ASSESS ATTENTION LEVEL AND CONTROL DRIVER’S ATTENTION
%U http://aircconline.com/ijcseit/V8N1/8118ijcseit02.pdf
%V 8
%X Any kind of vehicle driving is one of the most challenging tasks in this world requiring simultaneous
accomplishment of numerous sensory, cognitive, physical and psychomotor skills. There are various
number of factors are involved in automobile crash such as driver skill, behaviour and impairment due to
drugs, road design, vehicle design, speed of operation, road environment, notably speeding and street
racing. This study focuses a vision based framework to monitor driver’s attention level in real time by using
Microsoft Kinect for Windows sensor V2. Additionally, the framework generates an awareness signal to the
driver in case of low attention. The effectiveness of the system demonstrates through board experiments in
case of hostile light conditions also. Experimental result illustrates the quite well functionality of the
framework with 11 participants and measures the attention level of participants with equitable precision.
@article{noauthororeditor,
abstract = {Any kind of vehicle driving is one of the most challenging tasks in this world requiring simultaneous
accomplishment of numerous sensory, cognitive, physical and psychomotor skills. There are various
number of factors are involved in automobile crash such as driver skill, behaviour and impairment due to
drugs, road design, vehicle design, speed of operation, road environment, notably speeding and street
racing. This study focuses a vision based framework to monitor driver’s attention level in real time by using
Microsoft Kinect for Windows sensor V2. Additionally, the framework generates an awareness signal to the
driver in case of low attention. The effectiveness of the system demonstrates through board experiments in
case of hostile light conditions also. Experimental result illustrates the quite well functionality of the
framework with 11 participants and measures the attention level of participants with equitable precision. },
added-at = {2018-03-07T07:26:53.000+0100},
author = {Lata, Munira Akter and Rahman, Md Mahmudur and Yousuf, Mohammad Abu and Ananya, Md. Ibrahim Al and Roy, Devzani and Mahadi, Alvi},
biburl = {https://www.bibsonomy.org/bibtex/21b1335e57b9ade95fce6f8dec739bfda/ijcseit},
doi = {10.5121/ijcseit.2018.8102},
interhash = {3ade54ee15c3f044b5061dd4cf8e7d79},
intrahash = {1b1335e57b9ade95fce6f8dec739bfda},
issn = {2231 - 3117 [Online] ; 2231 - 3605 [Print]},
journal = {International Journal of Computer Science, Engineering and Information Technology(IJCSEIT)},
keywords = {(AE) (AF) (AM) (ES) (FA) (MM) (SDK) Angle Attention Development Eye Face Kinect Kit Motion Mouth Software State and with},
language = {English},
month = feb,
number = 1,
pages = {13-26},
timestamp = {2018-03-07T07:26:53.000+0100},
title = {DEVELOPMENT OF AN EMPIRICAL MODEL TO ASSESS ATTENTION LEVEL AND CONTROL DRIVER’S ATTENTION},
url = {http://aircconline.com/ijcseit/V8N1/8118ijcseit02.pdf},
volume = 8,
year = 2018
}