Abstract
In this work, we propose a new application for road moving object detection in the goal to participate in reducing the big number of road accidents. Road moving object detection in a traffic video is a difficult task. Hence, in this work we present a new system in order to control the outside car risks by detecting and tracking of different road moving objects. This developed system is based on computer vision techniques that aim to solve this problem by using Haar like features and Background Subtraction technique. Experimental results indicate that the suggested method of moving object detection can be achieved with a high detection ratio.
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References
Sivaraman, S., Trivedi M.: Looking at vehicles on the road: a survey of vision-based vehicle detection, tracking, and behavior analysis. IEEE Trans. Intell. Transp. Syst. 14(4), 1773–1795 (2013)
Sun, Z., Bebis, G., Miller, R.: On-road vehicle detection: a review. IEEE Trans. Pattern Anal. Mach. Intell. 28(5), 694–711 (2006)
Chaqueta, J.M., Carmonaa, E.J., Caballerob, A.F.: A survey of video datsets for human action and activity recognition. Comput. Vision Image Understaning 117(6), 633–659 (2013)
Kulchandani. J.S., Dargwala, K.J.: Moving object detection: Review Of recent research trends. In: IEEE International Conference on Pervasive Computing, pp. 1–5 (2015)
Paragios, N., Deriche. R.: Geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Trans. Pattern Anal. Mach. Intell. 22(3), 266–280 (2000)
Haritaoglu, I., Harwood, D., Davis, L.S.: W4: a real time system for detecting and tracking people. In: Computer Vision and Pattern Recognition, pp. 962–967 (1998)
Hu, W., Tan, T., Wang, L., Maybank, S.: A survey on visual surveillance of object motion and behaviors. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 34(3), 334–352 (2004)
Soharab, H.S., Khalid, S., Nabendu, C.: Moving object detection using background subtraction (2014). (Online). Available: http://link.springer.com/book/10.1007%2F978-3-319-07386-6
Mandellos, N.A., Keramitsoglou, I., Kiranoudis, C.T.: A background subtraction algorithm for detecting and tracking vehicles. Expert Syst. Appl. 1619–1621 (2011)
Piccardi, M.: Background subtraction techniques: a review. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 3099–3104 (2004)
Mignotte, M., Konrad. I.: Statistical background subtraction using spatial cues. Circuits Syst. Video Technol. IEEE Trans. 17(12), 1758–1763 (2007)
Neji, M., Wali, A., Alimi, A.M: Towards an intelligent information research system based on the human behavior: recognition of user emotional state. In: 12th IEEE/ACIS International Conference on Computer and Information Science, Japan (2013)
Ralph. O.M, Kong, S.G.: Senior member. In: Visual Analysis of Eye State and Head Pose for Driver Alertnes Monitoring, vol. 14, pp. 1462–1469. IEEE, USA (2013)
Wierwille, W.W, Ellsworth, L.A., Wreggit. S.S, Fairbanks. R.J and Kirn. C.L: Research on vehicle based driver status/performance monitoring: development, validation and refinement of algorithms for detection of driver drowsiness. National Highway Traffic Safety Administration, Technical report. DOT HS 808 247 (1994)
Viola, P., Jones, J.: Robust real-time face detection. Comput. Vision Pattern Recogn. 57(2), 137–154 (2001)
Geiger. A., Lauer, M., Wojek, C., Stiller, C. Urtasun, R.: 3D traffic scene understanding from movable platforms. In: Pattern Analysis and Machine Intelligence (PAMI) (2014)
Acknowledgements
The authors would like to acknowledge the financial support of this work by grants from the General Direction of Scientific Research (DGRST), Tunisia, under the ARUB program.
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Dkhil, M.B., Wali, A., Alimi, A.M. (2016). An Intelligent System for Road Moving Object Detection. In: Abraham, A., Han, S., Al-Sharhan, S., Liu, H. (eds) Hybrid Intelligent Systems. HIS 2016. Advances in Intelligent Systems and Computing, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-319-27221-4_16
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DOI: https://doi.org/10.1007/978-3-319-27221-4_16
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