'Owl' and 'Lizard': Patterns of head pose and eye pose in driver gaze classification

IET Computer Vision

Volumn 10, Issue 4, 2016, Pages 308-313

  Fridman, Lex ^a   Lee, Joonbum ^a   Reimer, Bryan ^a   Victor, Trent ^b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMOBILE DRIVERS; BIRDS; CLASSIFICATION (OF INFORMATION); DESIGN; EYE MOVEMENTS; MOTION ESTIMATION; TRACKING (POSITION);

CLASSIFICATION ACCURACY; GAZE TRACKING; HEAD POSE; MONOCULAR VIDEO; ON-ROAD STUDIES; POSE INFORMATION; VEHICLE INTERFACE;

ADVANCED DRIVER ASSISTANCE SYSTEMS;

EID: 84978116067     PISSN: 17519632     EISSN: 17519640     Source Type: Journal    
DOI: 10.1049/iet-cvi.2015.0296     Document Type: Article

References (25)

1. Klauer, S.G., Dingus, T.A., Neale, V.L., et al.: 'The impact of driver inattention on near-crash/crash risk: an analysis using the 100-car naturalistic driving study data'. Technical Report, National Highway Traffic Safety Administration, 2006
2. Liang, Y., Lee, J.D., Yekhshatyan, L.: 'How dangerous is looking away from the road? Algorithms predict crash risk from glance patterns in naturalistic driving', Hum. Factors J. Hum. Factors Ergon. Soc., 2012, 54, (6), pp. 1104- 1116
3. Senders, J.W., Kristofferson, A., Levison, W., et al.: 'The attentional demand of automobile driving', Highw. Res. Rec., 1967, 195, pp. 15-33
4. N.H.T.S. Administration et al.: 'Visual-manual NHTSA driver distraction guidelines for in-vehicle electronic devices' (National Highway Traffic Safety Administration (NHTSA), Department of Transportation (DOT), Washington, DC, 2012)
5. D. F.-T. W. Group et al.: 'Statement of principles, criteria and verification procedures on driver interactions with advanced in-vehicle information and communication systems'. Alliance of Automotive Manufacturers, 2006
6. Coughlin, J.F., Reimer, B., Mehler, B.: 'Monitoring, managing, and motivating driver safety and well-being', IEEE Pervasive Comput., 2011, 10, (3), pp. 14-21
7. Fridman, L., Langhans, P., Lee, J., et al.: 'Driver gaze region estimation without using eye movement', IEEE Intell. Syst., 2016, in press
8. Victor, T., Dozza, M., Bärgman, J., et al.: 'Analysis of naturalistic driving study data: safer glances, driver inattention, and crash risk', 2014
9. Lee, J., Muñoz, M., Fridman, L., et al.: 'Investigating drivers' head and glance correspondence', Transp. Res. F, Traffic Psychol. Behav., 2016, In press
10. Gaur, R.P., Jariwala, K.N.: 'A survey on methods and models of eye tracking, head pose and gaze estimation', J. Emerg. Technol. Innov. Res., JETIR, 2014, 1, (5), (October-2014), pp. 265-273
11. Sireesha, M., Vijaya, P., Chellamma, K.: 'A survey on gaze estimation techniques'. Proc. Int. Conf. on VLSI, Communication, Advanced Devices, Signals & Systems and Networking (VCASAN-2013), 2013, pp. 353-361
12. Kazemi, V., Sullivan, J.: 'One millisecond face alignment with an ensemble of regression trees'. 2014 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 1867-1874
13. Murphy-Chutorian, E., Trivedi, M.M.: 'Head pose estimation in computer vision: a survey', IEEE Trans. Pattern Anal. Mach. Intell., 2009, 31, (4), pp. 607-626
14. Al-Rahayfeh, A., Faezipour, M.: 'Eye tracking and head movement detection: a state-of-art survey', IEEE J. Translational Eng. Health Med., 2013, 1, pp. 2 100 212-2 100 212
15. Asadifard, M., Shanbezadeh, J.: 'Automatic adaptive center of pupil detection using face detection and CDF analysis'. Proc. Int. Multi Conf. of Engineers and Computer Scientists, 2010, vol. 1, p. 3
16. Mehler, B., Kidd, D., Reimer, B., et al.: 'Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems', Ergonomics, 2015, pp. 1-24
17. Smith, D., Chang, J., Glassco, R., et al.: 'Methodology for capturing driver eye glance behavior during in-vehicle secondary tasks', Transp. Res. Rec.: J. Transp. Res. Board, 2005, 1937, pp. 61-65
18. King, D.E.: 'Dlib-ml: a machine learning toolkit', J. Mach. Learn. Res., 2009, 10, pp. 1755-1758
19. Lienhart, R., Maydt, J.: 'An extended set of Haar-like features for rapid object detection'. Proc. 2002 Int. Conf. on Image Processing 2002, 2002, vol. 1, p. I- 900
20. Wagner, A., Wright, J., Ganesh, A., et al.: 'Toward a practical face recognition system: robust alignment and illumination by sparse representation', IEEE Trans. Pattern Anal. Mach. Intell., 2012, 34, (2), pp. 372-386
21. Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., et al.: '300 faces in-the-wild challenge: the first facial landmark localization challenge'. 2013 IEEE Int. Conf. on Computer Vision Workshops (ICCVW), 2013, pp. 397-403
22. Schweighofer, G., Pinz, A.: 'Globally optimal o (n) solution to the pnp problem for general camera models'. British Machine Vision Conf. (BMVC), 2008, pp. 1-10
23. Bradski, G., Kaehler, A.: 'Learning OpenCV: computer vision with the OpenCV library' (O'Reilly Media, Inc., 2008)
24. Pedregosa, F., Varoquaux, G., Gramfort, A., et al.: 'Scikit-learn: machine learning in Python', J. Mach. Learn. Res., 2011, 12, pp. 2825-2830
25. Batista, G.E., Prati, R.C., Monard, M.C.: 'A study of the behavior of several methods for balancing machine learning training data', ACM Sigkdd Explorations Newsl., 2004, 6, (1), pp. 20-29