Abstract
In the last few years, the application of ICT technologies in automotive field has taken an increasing role in improving both the safety and the driving comfort. In this context, systems capable of determining the traffic situation and/or driver behavior through the analysis of signals from multiple sensors (e.g. radar, cameras, etc...) are the subject of active research in both industrial and academic sectors. The extraction of contextual information through the analysis of video streams captured by cameras can therefore have implications in many applications focused both on prevention of incidents and on provision of useful information to drivers. In this paper, we investigate the study and implementation of algorithms for the extraction of context data from on-board cameras mounted on vehicles. A camera is oriented so as to frame the portion of road in front of the vehicle while the other one is positioned inside the vehicle and pointed on the driver.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Trivedi, M., Gandhi, T., McCall, J.: Looking-in and looking-out of a vehicle: Computer-vision-based enhanced vehicle safety. IEEE Transactions on Intelligent Transportation Systems 8(1), 108–120 (2007)
Murphy-Chutorian, E., Trivedi, M.M.: Head pose estimation in computer vision: A survey. IEEE Trans. Pattern Anal. Mach. Intell. 31(4), 607–626 (2009)
Smith, P., Shah, M., da Vitoria Lobo, N.: Determining driver visual attention with one camera. IEEE Transactions on Intelligent Transportation Systems 4(4), 205–218 (2003)
Asteriadis, S., Tzouveli, P., Karpouzis, K., Kollias, S.: Estimation of behavioral user state based on eye gaze and head pose-application in an e-learning environment. Multimedia Tools Appl. 41(3), 469–493 (2009)
Tu, J., Fu, Y., Huang, T.S.: Locating nose-tips and estimating head poses in images by tensorposes. IEEE Transaction on Circuits and Systems for Video Technology 19(1) (2009)
Bergasa, L.M., Nuevo, J., Sotelo, M., Barea, R., Lopez Guillen, M.L.: Real-time system for monitoring driver vigilance. IEEE Transactions on Intelligent Transportation Systems 7(1), 63–77 (2006)
McCall, J.C., Trivedi, M.M.: Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation. IEEE Transaction on Intelligent Transportation Systems 7(1), 20–37 (2006)
Yu, G., Xiao, X., Bai, J.: Analysis of vehicle surroundings and driver status from video stream based on a single PAL camera. In: 9th International Conference on Electronic Measurement and Instruments, 2009. ICEMI 2009, August 16–19, pp. 4-363 – 4-367 (2009)
Voisin, V., Avila, M., Emile, B., Begot, S., Bardet, J.-C.: Road markings detection and tracking usingn hough transform and kalman filter. In: Blanc-Talon, J., Philips, W., Popescu, D.C., Scheunders, P. (eds.) ACIVS 2005. LNCS, vol. 3708, pp. 76–83. Springer, Heidelberg (2005)
Schneider, J., Wilde, A., Naab, K.: Probabilistic approach for modeling and identifying driving situations. In: IEEE Intelligent Vehicles Symposium, June 4-6, pp. 343–348 (2008)
Wang, Y., Bai, L., Fairhurst, M.: Robust Road Modeling and Tracking Using Condensation. IEEE Transactions on Intelligent Transportation Systems 9(4), 570–579 (2008)
Canny, J.: A Computational Approach To Edge Detection. IEEE Trans. Pattern Analysis and Machine Intelligence 8, 679–714 (1986)
Hough, P.V.C.: Machine Analysis of Bubble Chamber Pictures. In: Proc. Int. Conf. High Energy Accelerators and Instrumentation (1959)
Duda, R.O., Hart, P.E.: Use of the Hough Transformation to Detect Lines and Curves in Pictures. Comm. ACM 15, 11–15 (1972)
Viola, P., Jones, M.: Robust real-time object detection. International Journal of Computer Vision (2002)
Shi, J., Tomasi, C.: Good features to track. Computer Vision and Pattern Recognition. In: Proceedings of IEEE Computer Society Conference on CVPR 1994, pp. 593–600 (1994)
Yilmaz, A., Javed, O., Shah, M.: Object tracking: A survey. ACM Comput. Surv. 38 (2006)
Oliver, N., Pentland, A.: Driver Behavior Recognition and Prediction in SmartCar. In: Proceedings of SPIE Aerosense2000 ’̈Enhanced and Synthetic Vision’̈, Orlando. Florida (April 2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ciardelli, L., Beoldo, A., Pasini, F., Regazzoni, C. (2010). Driver’s Behavior Assessment by On-board/Off-board Video Context Analysis. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13025-0_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-13025-0_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13024-3
Online ISBN: 978-3-642-13025-0
eBook Packages: Computer ScienceComputer Science (R0)