Abstract
Advanced Driver Assistance Systems are, due to their potentials regarding security and markets, in the focus of future developments within the automotive industry. The visual observation of the car interior is gaining attention due to the increasing efficiency of methods and technologies in digital image processing. Special weight is put on the visual driver observation, which measures diversion and fatigue of the driver and notifies about endangering behavior. This is accomplished by utilizing complex image-processing systems. The spatial positions and orientations of head and eyes are measured and evaluated. This report presents in detail and coherently the motivation and the current status of available approaches and systems. Following, a new concept for spatio-temporal modeling and tracking of partially rigid objects is developed and described. This concept is based on methods for spatio-temporal scene analysis, graph theory, adaptive information fusion and multi-hypothesis tracking. Our original contributions are the detailed representation of the available procedures and systems in this certain field and the development of a new concept and related prototypes.
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References
Baker, S., Matthews, I., Xiao, J., Gross, R., Kanade, T.: Real-Time Non-Rigid Driver Head Tracking For Driver Mental State Estimation. Pittsburgh, USA (2004)
Bretzner, L., Krantz, M.: Towards low-cost systems for measuring visual cues of driver fatigue and inattention in automotive applications. Göteborg, Sweden (2005)
Büker, U.: Innere Sicherheit in allen Fahrsituationen. Deutschland (2007)
Dankers, A., Zelinsky, A.: CeDAR: A real-world vision system. Mach. Vis. Appl. 16(1), 47–58 (2004)
European Commission, Directorate General Information Society and Media: Use of Intelligent Systems in Vehicles. Special Eurobarometer 267 / Wave 65.4 (2006)
Fu, Y., Huang, T.S.: Graph Embedded Analysis for Head Pose Estimation. In: The IEEE conference series on Automatic Face and Gesture Recognition (IEEE FG 2006), Southampton, UK, April 2006, pp. 3–8 (2006)
Gee, A.H., Cipolla, R.: Determining the gaze of faces in images. Cambridge, UK (1994)
Grammalidis, N., Strintzis, M.G.: Using 2-D and 3-D Ellipsoid Fitting for Head and Body Segmentation and Head Tracking. Thessaloniki, Greece (2000)
Grammalidis, N., Strintzis, M.G.: Head Detection and Tracking by 2-D and 3-D Ellipsoid Fitting. Thessaloniki, Greece (2000)
Haro, A., Flickner, M., Essa, I.: Detecting and Tracking Eyes By Using Their Physiological Properties, Dynamics, and Appearance. In: CVPR (2000)
Heinzmann, J., Zelinsky, A.: 3-D Facial Pose and Gaze Point Estimation using a Robust Real-Time Tracking Paradigm. Canberra, Australia (1997)
Isard, M., Blake, A.: CONDENSATION - conditional density propagation for visual tracking. Int. J. Computer Vision 29(1), 5–28 (1998)
Ji, Q., Zhu, Z., Lan, P.: Real-Time Nonintrusive Monitoring and Prediction of Driver Fatigue. IEEE Transactions on Vehicular Technology, 53(4) (July 2004)
Kähler, O., Denzler, J., Triesch, J.: Hierarchical Sensor Data Fusion by Probabilistic Cue Integration for Robust 3-D Object Tracking. Passau, Deutschland (2004)
Kropatsch, W.: Tracking with Structure in Computer Vision TWIST-CV. Pattern Recognition and Image Processing Group, TU Wien (2005)
Li, S.Z., Chu, R.F., Liao, S.C., Zhang, L.: Illumination Invariant Face Recognition Using Near-Infrared Images. IEEE Transaction on PAMI (Special issue on Biometrics: Progress and Directions) 29(4), 627–639 (2007)
Loy, G., Fletcher, L., Apostoloff, N., Zelinsky, A.: An Adaptive Fusion Architecture for Target Tracking. Canberra, Australia (2002)
Mak, K.: Analyzes Advanced Driver Assistance Systems (ADAS) and Forecasts 63M Systems For 2013. UK (2007)
van der Mark, W., Gavrila, D.M.: Real-Time Dense Stereo for Intelligent Vehicles. IEEE Transactions on Intelligent Transportation Systems 7(1) (March 2006)
Mills, S., Novins, K.: Motion Segmentation in Long Image Sequences. Dunedin, New Zealand (2000)
Mills, S., Novins, K.: Graph-Based Object Hypothesis. Dunedin, New Zealand (1998)
Mills, S.: Stereo-Motion Analysis of Image Sequences. Dunedin, New Zealand (1997)
Murphy-Chutorian, E., Trivedi, M.: Head Pose Estimation in Computer Vision: A Survey. IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI) (March 2008)
Ntawiniga, F.: Head Motion Tracking in 3D Space for Drivers. Departement De Genie Electrique Et De Genie Informatique, Faculte Des Sciences Et De Genie, Universite Laval, Quebec (2008)
Phillips, P.J.: FRVT 2006 and ICE 2006 Large-Scale Results (2007)
Potamianos, G., Zhang, Z.: A Joint System for Single-Person 2D-Face and 3D-Head Tracking in CHIL Seminars. New York, USA (2006)
Russakoff, D.B., Herman, M.: Head tracking using stereo. International Journal of Machine Vision and Applications 12(3), 164–173 (2002)
Scharstein, D., Szeliski, R.: A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. Middlebury and Redmond, USA (2003)
Seeing Machines: WIPO Patent (a) WO/2007/062478 (b) WO/2004/088348 (c) WO/2004/003849 (d) WO/2003/081532 (e) WO/2002/009025
SmartEye: WIPO Patent (a) WO/2003/003910 (b) WO/2002/089064 (c) WO/2002/049506
Smith, P., Shah, M., da Vitoria Lobo, N.: Determining Driver Visual Attention with One Camera. IEEE Transactions on Intelligent Transportation Systems 4(4) (December 2003)
Stankowitz, W.: Fahrerassistenzsysteme als beste Beifahrer. Deutschland (2007)
Triesch, J., von der Malsburg, C.: Democratic Integration: Self-Organized Integration of Adaptive Cues. Neural Computation 13(9), 2049–2074 (2001)
Williamson, A., Chamberlain, T.: Review of on-road driver fatigue monitoring devices. South Wales, UK (2005)
Yang, M.-H., Kriegman, D.J., Ahuja, N.: Detecting Faces in Images - A Survey. Mountain View, USA (2001)
Yang, M.-H.: Recent Advances in Face Detection. Mountain View, USA (2004)
Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face Recognition - A Literature Survey. Maryland, USA (2003)
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Steffens, M., Aufderheide, D., Kieneke, S., Krybus, W., Kohring, C., Morton, D. (2009). A New Approach on Spatio-temporal Scene Analysis for Driver Observation. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_63
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DOI: https://doi.org/10.1007/978-3-642-02611-9_63
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