Driver fatigue detection by fusing multiple cues

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4492 LNCS, Issue PART 2, 2007, Pages 801-809

  Senaratne, Rajinda ^a   Hardy, David ^a   Vanderaa, Bill ^a   Halgamuge, Saman ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; BAYESIAN NETWORKS; FACE RECOGNITION; FUZZY RULES; SUPPORT VECTOR MACHINES;

BAYES CLASSIFIER; MULTIPLE CUES;

FATIGUE OF MATERIALS;

EID: 37249046003     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72393-6_96     Document Type: Conference Paper

References (20)

1. Lal, S.K.L., Craig, A.: Driver Fatigue: Electroencephalography and Psychological Assessment. Psychophysiology 39(3) (2002) 313-321
2. Ji, Q., Zhu, Z.W., Lan, P.L.: Real-time Nonintrusive Monitoring and Prediction of Driver Fatigue. IEEE Trans. on Vehicular Technology 53(4) (2004) 1052-1068
3. Smith, P., Shah, M., Lobo, N.D.: Determining Driver Visual Attention with One Camera. IEEE Trans. on Intelligent Transportation Systems 4(4) (2003) 205-218
4. Bergasa, L.M., Nuevo, J., Sotelo, M.A., Barea, R., Lopez, M.E.: Real-time System for Monitoring Driver Vigilance. IEEE Trans. on Intelligent Transportation Systems 7(1) (2006) 63-77
5. Hartley, L., Horberry, T., Mabbott, N., Krueger, G. P.: Review of Fatigue Detection and Prediction Technologies. National Road Transport Commision, Melbourne (2000)
6. Senaratne, R., Halgamuge, S.: Optimised Landmark Model Matching for Face Recognition. In 7th International Conference on Automatic Face and Gesture Recognition (2006) 120-125
7. Senaratne, R., Halgamuge, S.: Optimal Weighting of Landmarks for Face Recognition. Journal of Multimedia 1(3) (2006) 31-41
8. Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. IEEE International Conference on Neural Networks 4 (1995) 1942-1948
9. Shi, Y., Eberhart, R.C.: Empirical Study of Particle Swarm Optimization. In Proc. of the IEEE Congress on Evolutionary Computation (1999) 1945-1950
10. Ratnaweera, A., Halgamuge, S.K., Watson, H.C.: Self-organizing Hierarchical Particle Swarm Optimizer with Time-varying Acceleration Coefficients. IEEE Trans. on Evolutionary Computation 8(3) (2004) 240-255
11. Siringa, L.: Eyes Detection for Face Recognition. Applied Artificial Intelligence. 7(4) (1993) 365-382
12. Baluja, S.: Using Labeled and Unlabeled Data for Probabilistic Modeling of Face Orientation. International Journal of Pattern Recognition and Artificial Intelligence 14(8) (2000) 1097-1107
13. Cortes, C., Vapnik, V.: Support-vector Networks. Machine Learning 20(3) (1995) 273-297
14. Chang, C.C., Lin, C.J.: LIBSVM: A Library for Support Vector Machines. Software available at http://www.csie.ntu.edu,tw/$\sim$cjlin/ libsvm (2001)
15. Popieul, J.C., Simon, P., Loslever, P.: Using Driver's Head Movements Evolution as A Drowsiness Indicator. In IEEE Intelligent Vehicles Symposium (2003) 616-621
16. Roge, J., Pebayle, T., Muzet, A.: Variations of the Level of Vigilance and of Behavioural Activities during Simulated Automobile Driving. Accident Analysis and Prevention 33(2) (2001) 181-186
17. Halgamuge, S.K.: Self-evolving Neural Networks for Rule-based Data Processing. IEEE Trans. on Signal Processing 45(11) (1997) 2766-2773
18. Halgamuge, S.K., Poechmueller, W., Glesner, M.: An Alternative Approach for Generation of Membership Functions and Fuzzy Rules based on Radial and Cubic Basis Function Networks. International Journal of Approximate Reasoning 12(3-4) (1995) 279-298
19. Halgamuge, S.K., Glesner, M.: Fuzzy Neural Networks - Between Functional Equivalence and Applicability. International Journal of Neural Systems 6(2) (1995) 185-196
20. Halgamuge, S.K.: A Trainable Transparent Universal Approximator for Defuzzification in Mamdani-type Neuro-fuzzy Controllers. IEEE Trans. on Fuzzy Systems 6(2) (1998) 304-314