Abstract:
Controlling multiple devices while driving steals drivers' attention from the road and is becoming the cause of accidents in 1 out of 3 cases. Many research efforts are b...Show MoreMetadata
Abstract:
Controlling multiple devices while driving steals drivers' attention from the road and is becoming the cause of accidents in 1 out of 3 cases. Many research efforts are being dedicated to design, manufacture and test Human-Machine Interfaces that allow operating car devices without distracting the drivers' attention. A complete system for controlling the infotainment equipment through hand gestures is explained in this paper. The system works with a visible-infrared camera mounted on the ceiling of the car and pointing to the shift-stick area, and is based in a combination of some new and some well-known computer vision algorithms. The system has been tested by 23 volunteers on a car simulator and a real vehicle and the results show that the users slightly prefer this system to an equivalent one based on a touch-screen interface.
Published in: 2014 IEEE Intelligent Vehicles Symposium Proceedings
Date of Conference: 08-11 June 2014
Date Added to IEEE Xplore: 17 July 2014
Electronic ISBN:978-1-4799-3638-0
Print ISSN: 1931-0587
References is not available for this document.
Select All
1.
Klauer, S. G., Guo, F., Sudweeks, J., & Dingus, T. A. (2010). An analysis of driver inattention using a case-crossover approach on 100-car data: Final report" (No. HS-811 334).
2.
McEvoy, S. P., Stevenson, M. R., & Woodward, M. "The impact of driver distraction on road safety: results from a representative survey in two Australian states." Injury prevention, 12(4), 242-247.2006 (Pubitemid 44274813)
3.
Pickering, C.A., "The search for a safer driver interface: a review of gesture recognition human machine interface," Computing & Control Engineering Journal, vol.16, no.1, pp.34,40, Feb.-March 2005
4.
Rümelin, S. & Butz, A. "How to make large touch screens usable while driving." In Proceedings of the ACM 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 48-55). October, 2013.
5.
Geiger. "BerLuhrungslose Bedienung von Infotainment-Systemen im Fahrzeug". PhD thesis, TU MLunchen, 2003
6.
Pfleging, B., Schneegass, S., & Schmidt, A. "Multimodal interaction in the car: combining speech and gestures on the steering wheel." In Proceedings of the ACM 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. pp. 155-162. October 2012.
7.
Askar, S., Kondratyuk, Y., Elazouzi, K., Kauff, P., & Schreer, O. "Vision-based skin-colour segmentation of moving hands for realtime applications." In IET Visual Media Production, 2004.(CVMP). 1st European Conference on. pp. 79-85.March, 2004 (Pubitemid 40954832)
8.
Zhu, X., Yang, J., & Waibel, A. "Segmenting hands of arbitrary color. In Automatic Face and Gesture Recognition," 2000. Proceedings. Fourth IEEE International Conference on. pp. 446-453, 2000
9.
Kolsch, M., & Turk, M. "Analysis of rotational robustness of hand detection with a viola-jones detector." In Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on. Vol. 3, pp. 107-110.2004
10.
Herrmann, E., Makrushin, A., Dittmann, J., Vielhauer, C., Langnickel, M., & Kraetzer, C. "Hand-movement-based in-vehicle driver/front-seat passenger discrimination for centre console controls." Image Processing: Algorithms and Systems VIII. Proceedings of the SPIE, Volume 7532, article id. 75320U, 9 pp. (2010).
11.
Althoff, F., Lindl, R., Walchshausl, L., & Hoch, S. "Robust multimodal hand-and head gesture recognition for controlling automotive infotainment systems." VDI BERICHTE, 1919, 187. BMW Group Research and Technology Hanauerstr. 46, 80992 Munich, Germany 2005.
12.
Cheng, S. Y., & Trivedi, M. M. "Vision-based infotainment user determination by hand recognition for driver assistance." Intelligent Transportation Systems, IEEE Transactions on,11(3), 759-764.2010
13.
Cheng, S. Y., Park, S. & Trivedi, M. M. "Multi-spectral and multiperspective video arrays for driver body tracking and activity analysis." CVIU, 106(2), 245-257. 2007 (Pubitemid 46670741)
14.
Mittal, A., Zisserman, A., & Torr, P. "Hand detection using multiple proposals".In BMVC 2011
15.
Van den Bergh, M., & Van Gool, L. "Combining RGB and ToF cameras for real-time 3D hand gesture interaction." In Applications of Computer Vision (WACV), 2011 IEEE Workshop on. pp. 66-72. January 2011.
16.
Kurakin, A., Zhang, Z., & Liu, Z. "A real time system for dynamic hand gesture recognition with a depth sensor." In Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. pp. 1975-1979. 2012
17.
Akyol S., Canzler U., Bengler K., Hahn W. "Gesture Control for Use in Automobiles" in Proceedings of the IAPR MVA 2000 Workshop on Machine Vision Applications, pp. 349-352, November 28-30, 2000, Tokyo
18.
Ohn-Bar, E.; Trivedi, M.M., "In-vehicle hand activity recognition using integration of regions," Intelligent Vehicles Symposium (IV), 2013 IEEE, vol., no., pp.1034,1039, 23-26 June 2013
19.
Ohn-Bar, E., & Trivedi, M. M. "The Power is in Your Hands: 3D Analysis of Hand Gestures in Naturalistic Video."IEEE Conference on Computer Vision and Pattern Recognition Workshops. Pp 912- 917, June 2013.
20.
OpenCV Documentation. http://www.opencv.org
21.
J. Canny, "A Computational Approach to Edge Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, June 1986
22.
Parada-Loira, F.; Alba-Castro, J.L., "Local Contour Patterns for fast traffic sign detection," Intelligent Vehicles Symposium (IV), 2010 IEEE, vol., no., pp.1,6, 21-24 June 2010
23.
Zivkovic, Z. "Improved adaptive Gaussian mixture model for background subtraction". In 17th International Conference on Pattern Recognition (ICPR 2014), Vol. 2, pp. 28-31. 2014.
24.
J. Matas, O. Chum, M. Urban and T. Pajdla, "Robust Wide Baseline Stereo from Maximally Stable Extremal Regions," Proc. 13th British Machine Vision Conf., pp. 384-393, 2002.