Deformable Face Fitting Based Drowsiness Detection in Real Time System
Abstract
Drowsiness is the state where a person is not able to perform any task at his/her optimum efficiency. Due to negative impacts of drowsiness on daily activities, drowsiness detection is important to prevent consequences. Non-intrusive computer vision techniques are the most suitable method to detect drowsiness. In this method, one camera is required to analyze facial features. Among various facial features, features around mouth and eye region are most reliable parameters. In this research, eye closure and yawning data are used for drowsiness detection. Once face is detected by cascade classifier with Haar features, then eyes and mouth are detected and tracked by deformable face fitting. From eye and mouth area, their state can be estimated which is used to detect drowsiness. This system is practically feasible because it is non-intrusive; also it is well suited in real time due to its adequate speed and accuracy.
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Lin, S.D.; Jia-Jen Lin; Chin-Yao Chung, "Sleepy Eye's Recognition for Drowsiness Detection," Biometrics and Security Technologies (ISBAST), 2013 International Symposium on , vol., no., pp.176,179, 2-5 July 2013
Abtahi, S.; Hariri, B.; Shirmohammadi, S., "Driver drowsiness monitoring based on yawning detection," Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE , vol., no., pp.1,4, 10-12 May 2011
Devi, M.S.; Choudhari, M.V.; Bajaj, P., "Driver Drowsiness Detection Using Skin Color Algorithm and Circular Hough Transform," Emerging Trends in Engineering and Technology (ICETET), 2011 4th International Conference on , vol., no., pp.129,134, 18-20 Nov. 2011
Ms. Jaya M. Jadhav; Ms. Deipali V. Gore, “Introducing Celebrities in an Images Using HAAR Cascade Algorithm,’’ International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 8, pp. 571-577,August 2013 ISSN: 2277 128X
Ping Wang; Lin Shen, "A method of detecting driver drowsiness state based on multi-features of face," Image and Signal Processing (CISP), 2012 5th International Congress on , vol., no., pp.1171,1175, 16-18 Oct. 2012
Rezaee, K.; Alavi, S.R.; Madanian, M.; Rasegh Ghezelbash, M.; Khavari, H.; Haddadnia, J., "Real-time intelligent alarm system of driver fatigue based on video sequences," Robotics and Mechatronics (ICRoM), 2013 First RSI/ISM International Conference on , vol., no., pp.378,383, 13-15 Feb. 2013
Singh, A.; Kaur, J., "Driver fatigue detection using machine vision approach," Advance Computing Conference (IACC), 2013 IEEE 3rd International , vol., no., pp.645,650, 22-23 Feb. 2013
Omidyeganeh, M.; Javadtalab, A.; Shirmohammadi, S., "Intelligent driver drowsiness detection through fusion of yawning and eye closure," Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS), 2011 IEEE International Conference on , vol., no., pp.1,6, 19-21 Sept. 2011
Viola, P.; Jones, M., "Rapid object detection using a boosted cascade of simple features," Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on , vol.1, no., pp.I-511,I-518 vol.1, 2001
Saragih, Jason M., Simon Lucey, and Jeffrey F. Cohn. "Deformable model fitting by regularized landmark mean-shift." International Journal of Computer Vision 91.2 (2011): 200-215
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