Methods for machine vision based driver monitoring applications

The scope of this thesis is to investigate the feasibility of techniques and methods, previously examined within the industry, for monitoring the driver's momentary distraction state and level of vigilance during a driving task. The study does not penetrate deeply into the fundamentals of the proposed methods but rather provides a multidisciplinary review by adopting new aspects and innovative approaches to state-of-art monitoring applications for adapting them to an in-vehicle environment. The hypotheses of this thesis states that detecting the level of distraction and/or fatigue of a driver can be performed by means of a set of image processing methods, enabling eye-based measurements to be fused with other safety-monitoring indicators such as lane-keeping performance or steering activity.

[1]  Michael T. Orchard,et al.  A comparative study of DCT- and wavelet-based image coding , 1999, IEEE Trans. Circuits Syst. Video Technol..

[2]  Lars Petersson,et al.  Vision in and out of Vehicles , 2003, IEEE Intell. Syst..

[3]  Johan Engström,et al.  Sensitivity of eye-movement measures to in-vehicle task difficulty , 2005 .

[4]  M. Gonzalez-Mendoza,et al.  Driver vigilance monitoring, a new approach , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[5]  Bill Gates.  The Road Ahead , 1960 .

[6]  Lisbeth Almén.  REDUCING THE EFFECTS OF DRIVER DISTRACTION: A COMPARISON OF DISTRACTION ALERTS ON DRIVER ATTENTION , 2003 .

[7]  Kenneth W. Bauer,et al.  Feature Selection for Predicting Pilot Mental Workload: A Feasibility Study , 2002 .

[8]  de Dick Waard,et al.  Proceedings 3rd International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design , 2008 .

[9]  Antonio García Dopico,et al.  A Precise Eye-Gaze Detection and Tracking System , 2003, WSCG.

[10]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Alessio Del Bue,et al.  Smart cameras with real-time video object generation , 2002, Proceedings. International Conference on Image Processing.

[12]  Bernhard Schölkopf,et al.  Support vector learning , 1997 .

[13]  Mohan M. Trivedi,et al.  Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation , 2006, IEEE Transactions on Intelligent Transportation Systems.

[14]  N. Papanikolopoulos,et al.  Driver activity monitoring through supervised and unsupervised learning , 2005, Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005..

[15]  Moshe Eizenman,et al.  THE IMPACT OF COGNITIVE DISTRACTION ON DRIVER VISUAL BEHAVIOUR AND VEHICLE CONTROL , 2002 .

[16]  Zhiwei Zhu,et al.  Real time and non-intrusive driver fatigue monitoring , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[17]  David Beymer,et al.  Person counting using stereo , 2000, Proceedings Workshop on Human Motion.

[18]  Johan Engström,et al.  Effects of visual and cognitive load in real and simulated motorway driving , 2005 .

[19]  Kutila Matti,et al.  DEVELOPMENT OF A DRIVER SITUATION ASSESSMENT MODULE IN THE AIDE PROJECT , 2005 .

[20]  D. Esteve,et al.  Driver hypovigilance diagnosis using wavelets and statistical analysis , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[21]  Minoru Fukumi.  Driver face monitoring using a near-infrared camera , 2005, SIP.

[22]  Fengliang Xu,et al.  Real-time eye detection and tracking for driver observation under various light conditions , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[23]  Ashley Craig,et al.  Development of an algorithm for an EEG-based driver fatigue countermeasure. , 2003, Journal of safety research.

[24]  John Swarbrooke,et al.  Case Study 18 – Las Vegas, Nevada, USA , 2007 .

[25]  Luke Fletcher,et al.  Computer Vision for Vehicle Monitoring and Control , 2001 .

[26]  Harini Veeraraghavan,et al.  DETECTING DRIVER FATIGUE THROUGH THE USE OF ADVANCED FACE MONITORING TECHNIQUES , 2001 .

[27]  P.M. O'Brien.  Eyeblink monitoring as a means of measuring pilot physiological state , 1988, Proceedings of the IEEE 1988 National Aerospace and Electronics Conference.

[28]  Martial Hebert,et al.  Spectro-polarimetric imager for intelligent transportation systems , 1998, Other Conferences.

[29]  Junghee Jun,et al.  Robust camera calibration using neural network , 1999, Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030).

[30]  Yi-Lin Chang,et al.  Wavelet transform coding for image sequence compression , 1995, Proceedings of IEEE Singapore International Conference on Networks and International Conference on Information Engineering '95.

[31]  Thomas A. Dingus,et al.  An overview of the 100-car naturalistic study and findings , 2005 .

[32]  Joao Dinis,et al.  Camera model and calibration process for high-accuracy digital image metrology of inspection planes , 1998, Other Conferences.

[33]  M. A. Recarte,et al.  Mental workload while driving: effects on visual search, discrimination, and decision making. , 2003, Journal of experimental psychology. Applied.

[34]  Angelos Amditis,et al.  Towards the Automotive HMI of the Future: Mid-Term Results of the AIDE Project , 2006 .

[35]  Mubarak Shah,et al.  Determining driver visual attention with one camera , 2003, IEEE Trans. Intell. Transp. Syst..

[36]  L. Andreone,et al.  Developing a near infrared based night vision system , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[37]  L. Uzych,et al.  Fast food restaurants. , 1996, Diabetes care.

[38]  T. Victor.  Keeping Eye and Mind on the Road , 2005 .

[39]  Cheng-Chin Chiang,et al.  A Neural-Based Surveillance System for Detecting Dangerous Non-frontal Gazes for Car Drivers , 2004, IEICE Trans. Inf. Syst..

[40]  Rashid Ansari,et al.  Eye tracking using Markov models , 2004, ICPR 2004.

[41]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[42]  Thomas A. Dingus,et al.  The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data , 2006 .

[43]  D. Dinges,et al.  EVALUATION OF TECHNIQUES FOR OCULAR MEASUREMENT AS AN INDEX OF FATIGUE AND THE BASIS FOR ALERTNESS MANAGEMENT , 1998 .

[44]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[45]  M. S. Stachowicz,et al.  Image segmentation and classification using color features , 2002, International Symposium on VIPromCom Video/Image Processing and Multimedia Communications.

[46]  Zhigang Zhang,et al.  3D intelligent sensing based on the PMD technology , 2001 .

[47]  Jean-Philippe Tarel,et al.  Automatic fog detection and estimation of visibility distance through use of an onboard camera , 2006, Machine Vision and Applications.

[48]  S. Bruce,et al.  Design and test of military cockpits , 1998, 1998 IEEE Aerospace Conference Proceedings (Cat. No.98TH8339).

[49]  Zhiwei Zhu,et al.  Active facial tracking for fatigue detection , 2002, Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings..

[50]  Ernest L. Hall,et al.  Automatic calibration and neural networks for robot guidance , 2003, SPIE Optics East.

[51]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[52]  T. D'Orazio,et al.  A neural system for eye detection in a driver vigilance application , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[53]  A. Sengupta,et al.  Compressing still and moving images with wavelets , 1994, Multimedia Systems.

[54]  L. Berthouze,et al.  A camera neural model , 1996, 1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929).

[55]  G. Ulsoy,et al.  On-line identification of driver state for lane-keeping tasks , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[56]  Chu Jiang-wei,et al.  A monitoring method of driver fatigue behavior based on machine vision , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[57]  J. Susan Milton,et al.  Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences , 1990 .

[58]  Gustav Markkula,et al.  Online detection of driver distraction: preliminary results from the AIDE project , 2005 .

[59]  Alessandro De Gloria,et al.  COMUNICAR: designing a multimedia, context-aware human-machine interface for cars , 2004, Cognition, Technology & Work.

[60]  R. C. Hughes,et al.  Review of Chemical Sensors for In-Situ Monitoring of Volatile Contaminants , 2001 .

[61]  S.R. Morrison.  Semiconducting-oxide chemical sensors , 1991, IEEE Circuits and Devices Magazine.

[62]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[63]  Lubomir Pousek,et al.  Detecting of Fatigue States of a Car Driver , 2000, ISMDA.

[64]  S. Welstead.  Fractal and Wavelet Image Compression Techniques , 1999 .

[65]  Mubarak Shah,et al.  Monitoring head/eye motion for driver alertness with one camera , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[66]  M.M. Trivedi,et al.  Visual context capture and analysis for driver attention monitoring , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[67]  Miguel Ángel Sotelo,et al.  Real-time system for monitoring driver vigilance , 2004, Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005..

[68]  L. Petersson,et al.  Road scene monotony detection in a fatigue management driver assistance system , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[69]  Slobodan Ilic,et al.  In-vehicle data logging system for fatigue analysis of drive shaft , 2004, International Workshop on Robot Sensing, 2004. ROSE 2004..

[70]  Hanqi Zhuang,et al.  Camera-aided robot calibration , 1996 .

[71]  M. Goodale,et al.  The visual brain in action , 1995 .

[72]  B. Carnahan,et al.  A drowsy driver detection system for heavy vehicles , 1998, 17th DASC. AIAA/IEEE/SAE. Digital Avionics Systems Conference. Proceedings (Cat. No.98CH36267).

[73]  Shin Yamamoto,et al.  Driver blink measurement by the motion picture processing and its application to drowsiness detection , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[74]  Osama Masoud,et al.  Vision-based methods for driver monitoring , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[75]  Antonio Pardo Martínez,et al.  Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts , 1998 .

[76]  Dot Hs,et al.  The 100 Car Naturalistic Driving Study , 2002 .

[77]  Donald L. Fisher,et al.  Verbal and Spatial Loading Effects on Eye Movements in Driving Simulators: A Comparison to Real World Driving , 2002 .

[78]  A. Manduca.  Compressing images with wavelet/subband coding , 1995 .

[79]  T. Zrimec.  Toward automatic colour calibration using machine learning , 2003, IEEE International Conference on Industrial Technology, 2003.

[80]  Thorsten Joachims,et al.  Making large scale SVM learning practical , 1998 .

[81]  Wang Rongben,et al.  Monitoring mouth movement for driver fatigue or distraction with one camera , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[82]  M. Eriksson,et al.  Eye-tracking for detection of driver fatigue , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[83]  Nikolaos Papanikolopoulos,et al.  Monitoring driver fatigue using facial analysis techniques , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[84]  Alessandro Verri,et al.  Learning and vision machines , 2002, Proc. IEEE.