Open Access Open Access  Restricted Access Subscription or Fee Access

Deformable Face Fitting Based Drowsiness Detection in Real Time System

Dipal M. Sodha, Kiran Trivedi, Dr. Dipesh Kamdar

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.


Keywords


Drowsiness; Eye Closure; Eye Detection; Face Detection; Mouth Detection; Yawning

Full Text:

PDF

References


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

http://www.mathopenref.com/coordpolygonarea.html


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.