Eye Gesture Analysis with Head Movement for Advanced Driver Assistance Systems
Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.
[1] WHO, "World Health Report, Technical Report", World Health
Organisation, http://www.who.int/whr2001/2001/main/en/index.html,
2001.
[2] OECD, "Organisation for Economic Co-operation and Development,
Factbook 2006 - Economic", Environment and Social Statistics: Quality
of life. http://www.sourcecd.org, December, 2006.
[3] Department for Transportation, "-Reported Road Casualties Great
Britain 2008-Annual Report", (Online). Available
http://webarchive.nationalarchives.gov.uk/20110503151558/http://dft.go
v.uk/pgr/statistics/datatablespublications/accidents/casualtiesgbar/rrcgb2
008., 2008.
[4] National Highway Traffic Safety Administration, "National Motor
Vehicle Survey Crash Causation: Report to Congress", www.nhtsa.gov,
pp. 35, July, 2008.
[5] Neale, V. L. "Overview of the 100-Car Naturalistic study and findings",
Proceedings of the International Conference on Enhanced Safety of
Vehicles, 2005.
[6] Fletcher, L. and Zelinsky, A., "Driver Inattention Detection based on
Eye Gaze-Road Event Correlation", International Journal of Robotics,
pp. 774-801, 2009.
[7] MohdZaid, S.N.H., Mohamed A.M, and Soliman, A.H., "Towards Eye
Gesture Analysis for Driver Assistance System using Template
Matching",Proceeding of the 4th Engineering Conference, Malaysia,
2011.
[8] Jim Horne and Louise Rayner, "Sleep Related Vehicle Accidents,
Laboratory", Sleep Research,Loughborough University, 2000
[9] Flores, M., J., Armingol, J., M., and Escalera, A., "Real Time Warning
System for Driver Drowsiness Detection Using Visual Information,
Journal of Intelligent and Robotic", vol.59, no.2, 2010.
[10] Kutila, M., Jokela, M., Markkula, G., Rue, R.M.,"Driver Distraction
Detection With A Camera Vision System", IEEE International
Conference on Image Processing ICIP, pp.201-204, 2007.
[11] Kircher, K., Ahlstrom, C., Kircher, A., "Comparison of Two Eye Gaze
Based Real-Time Driver Distraction Detection Algorithms in A Small -
Scale Field Operational Test", Proceedings of Fifth International Driving
Symposium on Human Factors in Driver Assessment , Training and
Vehicle Design, pp.16-23, 2009.
[12] Royal Society for the Prevention of Accident (ROSPA), "What are the
most cause of Road Accident", (Online).Available
http://www.rospa.com/faqs/detail.aspx?faq=298. , 2011.
[13] Gejgus P. and Sparka M., "Face Tracking in Color Video Sequences",
Proceedings of the 19th Spring Conference on Computer Graphics,
Slovakia,pg. 268-273, 2003.
[14] Cannolly,C.,"Driver Assistance Systems Aim to Halve Traffic
Accidents--, Journal of Drivers, Transportation safety, Road safety,
Motorways, Car, vol. 29, no.1, pg. 13-19, 2009.
[15] Batista, J., "A Drowsiness and Point of Attention Monitoring System for
Driver Vigilance", Proceedings IEEE Intelligent Transportation Systems
Conference, pp.702 - 708, 2007, USA.
[16] Swain, M.J., and Ballard, D.H.,"Color Indexing--, International Journal
of Computer Vision, vol. 7, no. 1, pp. 11-32, 1991.
[17] Bergasa, L., M., Nuevo, J., Sotelo, M., A., Barea, R., and Lopez, M., E.,
"Real Time System for Monitoring Driver Vigilance", IEEE
Transactions on Intelligent Transportation Systems, vol. 7, no. 1, pp.63-
77, 2006.
[18] Knipling, R., and Rau, P., "PERCLOS : A Valid Psycho physiological
Measure of Alertness as Assessed by Psychomotor Vigilance"
(Online).Available from : www.fmcsa.dot.gov/documents/tb98-006.pdf,
1994.
[19] Gee, A. H. and Cipolla, R., "Determining the Gaze of Faces in Images",
Image and Vision Computing, vol.12,no. 10, pp.639-647, 1994.
[1] WHO, "World Health Report, Technical Report", World Health
Organisation, http://www.who.int/whr2001/2001/main/en/index.html,
2001.
[2] OECD, "Organisation for Economic Co-operation and Development,
Factbook 2006 - Economic", Environment and Social Statistics: Quality
of life. http://www.sourcecd.org, December, 2006.
[3] Department for Transportation, "-Reported Road Casualties Great
Britain 2008-Annual Report", (Online). Available
http://webarchive.nationalarchives.gov.uk/20110503151558/http://dft.go
v.uk/pgr/statistics/datatablespublications/accidents/casualtiesgbar/rrcgb2
008., 2008.
[4] National Highway Traffic Safety Administration, "National Motor
Vehicle Survey Crash Causation: Report to Congress", www.nhtsa.gov,
pp. 35, July, 2008.
[5] Neale, V. L. "Overview of the 100-Car Naturalistic study and findings",
Proceedings of the International Conference on Enhanced Safety of
Vehicles, 2005.
[6] Fletcher, L. and Zelinsky, A., "Driver Inattention Detection based on
Eye Gaze-Road Event Correlation", International Journal of Robotics,
pp. 774-801, 2009.
[7] MohdZaid, S.N.H., Mohamed A.M, and Soliman, A.H., "Towards Eye
Gesture Analysis for Driver Assistance System using Template
Matching",Proceeding of the 4th Engineering Conference, Malaysia,
2011.
[8] Jim Horne and Louise Rayner, "Sleep Related Vehicle Accidents,
Laboratory", Sleep Research,Loughborough University, 2000
[9] Flores, M., J., Armingol, J., M., and Escalera, A., "Real Time Warning
System for Driver Drowsiness Detection Using Visual Information,
Journal of Intelligent and Robotic", vol.59, no.2, 2010.
[10] Kutila, M., Jokela, M., Markkula, G., Rue, R.M.,"Driver Distraction
Detection With A Camera Vision System", IEEE International
Conference on Image Processing ICIP, pp.201-204, 2007.
[11] Kircher, K., Ahlstrom, C., Kircher, A., "Comparison of Two Eye Gaze
Based Real-Time Driver Distraction Detection Algorithms in A Small -
Scale Field Operational Test", Proceedings of Fifth International Driving
Symposium on Human Factors in Driver Assessment , Training and
Vehicle Design, pp.16-23, 2009.
[12] Royal Society for the Prevention of Accident (ROSPA), "What are the
most cause of Road Accident", (Online).Available
http://www.rospa.com/faqs/detail.aspx?faq=298. , 2011.
[13] Gejgus P. and Sparka M., "Face Tracking in Color Video Sequences",
Proceedings of the 19th Spring Conference on Computer Graphics,
Slovakia,pg. 268-273, 2003.
[14] Cannolly,C.,"Driver Assistance Systems Aim to Halve Traffic
Accidents--, Journal of Drivers, Transportation safety, Road safety,
Motorways, Car, vol. 29, no.1, pg. 13-19, 2009.
[15] Batista, J., "A Drowsiness and Point of Attention Monitoring System for
Driver Vigilance", Proceedings IEEE Intelligent Transportation Systems
Conference, pp.702 - 708, 2007, USA.
[16] Swain, M.J., and Ballard, D.H.,"Color Indexing--, International Journal
of Computer Vision, vol. 7, no. 1, pp. 11-32, 1991.
[17] Bergasa, L., M., Nuevo, J., Sotelo, M., A., Barea, R., and Lopez, M., E.,
"Real Time System for Monitoring Driver Vigilance", IEEE
Transactions on Intelligent Transportation Systems, vol. 7, no. 1, pp.63-
77, 2006.
[18] Knipling, R., and Rau, P., "PERCLOS : A Valid Psycho physiological
Measure of Alertness as Assessed by Psychomotor Vigilance"
(Online).Available from : www.fmcsa.dot.gov/documents/tb98-006.pdf,
1994.
[19] Gee, A. H. and Cipolla, R., "Determining the Gaze of Faces in Images",
Image and Vision Computing, vol.12,no. 10, pp.639-647, 1994.
@article{"International Journal of Business, Human and Social Sciences:62338", author = "Siti Nor Hafizah bt Mohd Zaid and Mohamed Abdel Maguid and Abdel Hamid Soliman", title = "Eye Gesture Analysis with Head Movement for Advanced Driver Assistance Systems", abstract = "Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.
", keywords = "Head rotation, Eye-gestures,Windscreen, Template
matching.", volume = "6", number = "6", pages = "1562-7", }
