References
- S.H. Lee, J. Choi, and J. Park, "Interactive e-Learning System Using Pattern Recognition and Augmented Reality," IEEE Trans. Consum. Electron., vol. 55, no. 2, May 2009, pp. 883-890. https://doi.org/10.1109/TCE.2009.5174470
- B. Choi et al., "A Metadata Design for Augmented Broadcasting and Testbed System Implementation," ETRI J., vol. 35, no. 2, Apr. 2013, pp. 292-300. https://doi.org/10.4218/etrij.13.0112.0412
- N. Parimal et al., "Application of Sensors in Augmented Reality Based Interactive Learning Environments," IEEE Int. Conf. ICST, Dec. 2012, pp. 173-178.
- M.A. Oikawa et al., "AR-Based Video-Mediated Communication: A Social Presence Enhancing Experience," 14th Int. Symp. VR, May. 2012, pp. 125-130.
- Y.M. Aung and A. Al-Jumaily, "AR Based Upper Limb Rehabilitation System," IEEE Int. Conf. BioRob., June 2012, pp. 213-218.
- T. Zysk, J. Luce, and J. Cunningham, "Augmented Reality for Precision Navigation," GPS World Mag., vol. 23, issue 6, June 2012, pp. 47-51.
- H. Chen et al., "Application of Augmented Reality in Engineering Graphics Education," IEEE Int. Symp. ITME 2, art. no. 6132125, Dec. 2011, pp. 362-365.
- Y.C. Cheng et al., "AR-Based Positioning for Mobile Devices," Int. Conf. Parallel Process., no. 6047276, Sept. 2011, pp. 63-70.
- J.J. Mccorvey, "Using Augmented Reality to Market Your Business," Inc., Apr. 2010. http://www.inc.com/magazine/ 20100401/using-augmented-reality-to-market-your-business.html
- Siemens, "From Sedans to Compact Cars - One HUD Fits All," press photo, reference no. 200605004, Siemens AG, Munich, Germany, 2006. http://www.siemens.com/press/en/presspicture/? press=/en/pp_sv/2006/sv200605004_(hud)_1376467.htm
- J. Lincoln, D. Lincoln, and M. Carmean, How a Laser HUD Can Make Driving Safer, MicroVision Program Brief, MicroVision, Inc., Mar. 2007.
- R. Parasuraman, R. Molloy, and I.L. Singh, "Performance Consequences of Automation-Induced Complacency," Int. J. Aviation Psychology, vol. 3, no. 1, 1993, pp. 1-23. https://doi.org/10.1207/s15327108ijap0301_1
- NHTSA, Measuring Distraction Potential of Operating In-Vehicle Devices, no. DOT-HS-811-231, Dec. 2008.
- S.C. Lee, "Psychological Effects on Aged Driver's Traffic Accidents," Korea J. Psychological Soc. Issues, vol. 12, 2006, pp. 149-167.
- Y. Zhang, Y. Owechko, and J. Zhang, "Learning-Based Driver Workload Estimation," Comput. Intell. Automobile Appl., Ser. Studies Comput. Intell., vol. 132, 2008, pp. 1-24.
- E.R. Michael, J.G. Leo, and J.W. Nicholas, "Effects of Naturalistic Cell Phone Conversations on Driving Performance," Int. J. Safety Research, vol. 35, 2004, pp. 453-464. https://doi.org/10.1016/j.jsr.2004.06.003
- E. Adella, A. Varhely, and M. Fontana, "The Effects of a Driver Assistance System for Safe Speed and Safe Distance: A Real-Life Field Study," Int. J. Transp. Research Part C 19, 2011, pp. 145-155. https://doi.org/10.1016/j.trc.2010.04.006
- E. Johan, J. Emma, and O. Joakim, "Effects of Visual and Cognitive Load in Real and Simulated Motorway Driving," Int. J. Transp. Research Part F, vol. 8, 2005, pp. 97-120. https://doi.org/10.1016/j.trf.2005.04.012
- R. Venkatasawmy, The Digitization of Cinematic Visual Effects: Hollywood's Coming of Age, UK: Press Lexington Books, 2013.
- A.S. Cohen and R. Hirsig, Feed Forward Programming of Car Driver's Eye Movement Behavior: A System Theoretical Approach, final technical report, vol. 2, 1980, pp. 1-223.
- V. Charissis and S. Papanastasiou, "Human-Machine Collaboration through Vehicle Head Up Display Interface," Int. J. Cognition, Technol., Work, vol. 12, no. 1, 2010, pp. 41-50. https://doi.org/10.1007/s10111-008-0117-0
- Y.C. Shinko, D. Anup, and M.T. Mohan, "Active Heads-up Display Based Speed Compliance Aid for Driver Assistance: A Novel Interface and Comparative Experimental Studies," IEEE Int. Symp. IV, 2007, pp. 594-599.
- A. Sato et al., "Visual Navigation System on Windshield Head-Up Display," Proc. 13th World Congress ITS, 2006, pp. 167-175.
- H. Watanabe et al., "The Effect of HUD Warning Location on Driver Responses," Proc. 6th World Congress ITS, 1999, pp. 1-10.
- C. Jablonski, "An Augmented Reality Windshield from GM," Mar. 2010. http://www.zdnet.com/blog/emergingtech/anaugmented- reality-windshield-from-gm/2164
- V. Poortere et al., "Efficient Pedestrian Detection: A Test Case for SVM Based Categorization," Proc. ICVW, Sept. 2002, pp. 19-20.
- D.M. Gavrila and V. Philomin, "Real-Time Object Detection for Smart Vehicles," IEEE Int. Conf. CVPR, 1999, pp. 87-93.
- S. Hermann and R. Klette, "Iterative Semi-Global Matching for Robust Driver Assistance Systems," Int. Conf. ACCV, vol. 7726, 2012, pp. 456-478.
- H. Hattori et al., "Stereo-Based Pedestrian Detection Using Multiple Patterns," Int. Conf. BMVC, 2009, pp. 1-10.
- M. Bajracharya et al., "A Fast Stereo-Based System for Detecting and Tracking Pedestrians from a Moving Vehicle," Int. J. Robotics Research, vol. 28, 2009, pp. 1466-1485. https://doi.org/10.1177/0278364909341884
- A. Shashua, Y. Gdalyahu, and G. Hayun, "Pedestrian Detection for Driving Assistance Systems: Single-Frame Classification and System Level Performance," IEEE Int. Symp. IV, 2004, pp. 1-6.
- S. Munder and D.M. Gavrila, "An Experimental Study on Pedestrian Classification," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 11, 2006, pp. 1863-1868. https://doi.org/10.1109/TPAMI.2006.217
- Australian Transport Council, The National Road Safety Strategy 2011-2020, 2011, pp. 1-108.
- K.H. Won and S.K. Jung, "Billboard Sweep Stereo for Obstacle Detection in Road Scenes," Int. J. IET, vol. 48, issue 24, Nov. 2012, pp. 1528-1530.
- M.W. Park, K.H. Won, and S.K. Jung, "Vehicle Detection and Tracking Using Billboard Sweep Stereo Matching Algorithm," Korea J. KMMS, vol. 16, no. 6, 2013, pp. 764-781.
- Z.H. Zhou and X. Geng, "Projection Functions for Eye Detection," Int. J. Pattern Recognition, vol. 37, no. 5, 2004, pp. 1049-1056. https://doi.org/10.1016/j.patcog.2003.09.006
- C. Cortes and V. Vapnik, "Support-Vector Networks," Int. J. Mach. Learning, vol. 20, no. 3, 1995, pp. 273-297.
- T. Joachims, "Making Large-Scale SVM Learning Practical," Advances in Kernel Methods - Support Vector Learning, B. Scholkopf, C. Burges, and A. Smola, Eds., Cambridge, MA: MIT Press, 1999.
- K.A. Paul and H. Ayman, "A Comparative Analysis between Rigorous and Approximate Approaches for LiDAR System Calibration," Korea J. KSGPC, vol. 30, no. 6, 2012, pp. 593-605.
- Wikipedia, Precision and recall. http://en.wikipedia.org/wiki/ Precision_and_recall
- Gamedev.net, Calculate framerate with GetTickCount function. http://www.gamedev.net/topic/621703-calculate-framerate-withgettickcount/
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