Browse > Article
http://dx.doi.org/10.17661/jkiiect.2017.10.2.133

A Study on the automatic vehicle monitoring system based on computer vision technology  

Cheong, Ha-Young (Corporation e-oasis)
Choi, Chong-Hwan (Department Aerodefense&Information Communication, Daeduk College)
Choi, Young-Gyu (Department of Computer Engineering, Korea National University of Transportation)
Kim, Hyon-Yul (Department of Automotive Engineering, Osan University)
Kim, Tae-Woo (Korea Polytechnic III)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.10, no.2, 2017 , pp. 133-140 More about this Journal
Abstract
In this paper, we has proposed an automatic vehicle monitoring system based on computer vision technology. The real-time display system has displayed a system that can be performed in automatic monitoring and control while meeting the essential requirements of ITS. Another advantage has that for a powerful vehicle tracking, the main obstacle handing system, which has the shadow tracking of moving objects. In order to obtain all kinds of information from the tracked vehicle image, the vehicle must be clearly displayed on the surveillance screen. Over time, it's necessary to precisely control the vehicle, and a three-dimensional model-based approach has been also necessary. In general, each type of vehicle has represented by the skeleton of the object or wire frame model, and the trajectory of the vehicle can be measured with high precision in a 3D-based manner even if the system has not running in real time. In this paper, we has applied on segmentation method to vehicle, background, and shadow. The validity of the low level vehicle control tracker was also detected through speed tracking of the speeding car. In conclusion, we intended to improve the improved tracking method in the tracking control system and to develop the highway monitoring and control system.
Keywords
Computer vision; Automatic traffic; HMM based segmentation method; Real-time; Robust car image plane; Ground plane;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 A. Blake and M. Isard, Active contours, Springer, 1998.
2 A.P. Dempster, N.M. Laird, and D.R. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J.R. Stat. Soc., B 39, pp. 1-38, 2006.
3 S. Kamijo, Y. Matsushita, K. Ikeuchi, and M. Sakauchi, "Occlusion robust tracking utilizing spatio-temporal Markov Random Field model," IEICE Trans. Inf. & Syst. (Japanese Edition), vol.J83-D-II, no.12, pp.2597-2609, Dec. 2008.
4 J. Kato, T. Watanabe, and M. Yoneda, "HMM-based back-ground-object-shadow separation for traffic monitoring movies," Trans. IPS Japan, vol.42, no.l, pp.1-15, 2009.
5 J. Kato, T. Watanabe, S. Joga, J. Rittscher, and A. Blake, "An HMM-based segmentation method for traffic monitoring movies," IEEE Trans. Pattern Anal. & Mach. Intell., vol.24, no.9, pp.1291-1296, 2009.
6 J. Li, A. Najmi, and R.M. Gray, "Image classification by a two-dimensional hidden Markov model," IEEE Trans. Signal Processing, vol.48, no.2, pp.517-533, 2010.
7 K. Maeda, K. Onoguchi, K. Fukui, and Y. Taniguchi, "Computer vision application to ITS," J. IEICE, vol.83, no.3, pp.191-195, 2012.
8 I.D. Reid, D.W. Murray, and K.J. Bradshaw, "Towards active exploration of static and dynamic scene geometry," IEEE Int'l Conference on Robotics and Automation, San Diego CA, 2013.
9 S. Takaba, "Significance of ITS and formation of its basic concept," J. IEICE, vol.83, no.7, pp.528-530, 2014
10 S. Yun, H. Son, Y. Rhee, "A Study of Intelligent Head Up Display System for Next Generation Vehicle," The Journal of Korea Institute of Information, Electronics, and Communication Technology, No. 4, Vol. 1, pp.23-31, 2011.03
11 H, Park, "Vehicle Tracking System using HSV Color Space at nighttime," The Journal of Korea Institute of Information, Electronics, and Communication Technology, No. 8, Vol. 4, pp.270-274, 2015.08   DOI
12 K.D. Baker and G.D. Sullivan, "Performance assessment of model-based tracking," Proc. IEEE Workshop on Applications of Computer Vision, pp.28-35, Palm Springs, CA, 1992.
13 S. Rowe and A. Blake, "Statistical mosaics for tracking, 5, Image and Vision Computing, vol. 14, pp.549-564, 1996.   DOI
14 L.E. Baum, T. Petrie, G. Soules, and N. Weiss, "A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains, J, Ann. Math. Stat., vol.41, no.l ,pp.164-171, 1970.   DOI