吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (04): 866-870.doi: 10.7964/jdxbgxb201304004

• paper • Previous Articles     Next Articles

Developing a smart camera for mixed traffic flow detection

WEI Wei1, LI Zhi-hui1, ZHAO Yong-hua2, QU Zhao-wei1, JIANG Sheng1, CHAI Ting-ting1   

  1. 1. College of Transportation, Jilin University, Changchun 130022,China;
    2. Center of Computer Teaching and Research, Jilin University, Changchun 130022,China
  • Received:2012-11-26 Online:2013-07-01 Published:2013-07-01

RICH HTML

0   

PDF (PC)

313

Abstract:

Smart cameras in detection of mixed traffic flow parameters are in shortage. This creates a huge load of communication between the cameras and monitoring center. To solve this problem, this paper proposes a method of hardware and software codesign and implementation of a smart camera platform to detect mixed traffic flow parameters. Charge-coupled Device (CCD) camera sensor and Digital Signal Processor (DSP) are used to construct the camera hardware prototype. The video processing methods including background initialization, background model, foreground obtaining, image segmentation, pattern extraction, multi-classification etc. are used to construct the software system. Experiments were conducted under different mixed traffic conditions to test the camera system. Results show that this system can accurately obtain mixed traffic flow parameters. This study provides a reference for the development of smart camera system for mixed traffic detection.

Key words: engineering of communication and transportation system, video detection, mixed traffic flow, smart camera

CLC Number: 

  • U121

[1] Bramberger M, Brunner J, Rinner B,et al. Real-time video analysis on an embedded smart camera for traffic surveillance//In: Real-Time and Embedded Technology and Applications Symposium, 2004 Proceedings RTAS 2004 10th IEEE,2004:174-181.

[2] Bramberger M, Roman P Pflugfelder, Maier Arnold,et al. A smart camera for traffic surveillance//Proceedings of the First Workshop on Intelligent Solutions in Embedded Systems; 2003; Vienna University of Technology, Austria; 2003:153-164.

[3] Arth C, Bischof H, Leistner C. TRICam-an embedded platform for remote traffic surveillance//Computer Vision and Pattern Recognition Workshop, 2006 CVPRW '06 Conference on, 2006:125.

[4] Wei Bei-na, Shi Yu,Ye Ge-tian ,et al. Developing a smart camera for road traffic surveillance//Multimedia Signal Processing, 2008 IEEE 10th Workshop on,2008:826-831.

[5] Houben Q, Czyz J, Diaz J C Tocino,et al. Feature-based stereo vision using smart cameras for traffic surveillance//Fritz M, Schiele B, Piater JH, eds. Computer Vision Systems, Proceedings; 2009:144-153.

[6] Macesic M, Jelaca V, Nino-Castaneda J O. et al. Real-time detection of traffic events using smart cameras//In: Proceedings of SPIE-IS and T Electronic Imaging-Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques,Burlingame, CA, United states, 2012.

[7] 李志慧, 张长海, 曲昭伟,等. 交通流视频检测中背景模型与阴影检测算法[J]. 吉林大学学报:工学版, 2006, 36(6): 993-997. Li Zhi-hui, Zhang Chang-hai, Qu Zhao-wei,et al. Background extraction model and shadow detection algorithm in traffic flow video detection[J]. Journal of Jilin University (Engineering and Technology Edition),2006, 36(6): 993-997.

[8] Stauffer Chris, Grimson W E L. Adaptive background mixture models for real-time tracking[J]. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition,1999, 2(Compendex): 246-252.

[9] 李志慧, 张长海, 曲昭伟,等. 交通流视频检测中背景初始化算法[J]. 吉林大学学报:工学版, 2008,38(1): 148-151. Li Zhi-hui, Zhang Chang-hai, Qu Zhao-wei, et al. Background initialization algorithm in traffic flow video detection[J]. Journal of Jilin University (Engineering and Technology Edition),2008, 38(1): 148-151.

[10] 曲昭伟, 陈红艳, 李志慧,等. 基于单模板的二维场景重建方法[J]. 吉林大学学报:工学版,2007,37(5): 1159-1163. Qu Zhao-wei, Chen Hong-yan, Li Zhi-hui,et al. 2D view reconstruction method based on single calibration pattern[J]. Journal of Jilin University (Engineering and Technology Edition),2007, 37(5): 1159-1163.

[11] Cortes Corinna, Vapnik Vladimir. Support-vector networks[J]. Machine Learning, 1995, 20(3): 273-297.

[12] Scholkopf B, Smola A J, Williamson R C,et al. New support vector algorithms[J]. Neural Computation, 2000, 12(5): 1207-1245.

[13] Scholkopf B, Platt J C, Shawe-Taylor J,et al. Estimating the support of a high-dimensional distribution[J]. Neural Computation, 2001, 13(7): 1443-1471.

[14] Rangel Pedro, Lozano Fernando, Garcia Elkin. Boosting of support vector machines with application to editing//ICMLA 2005: 4th International Conference on Machine Learning and Applications, Los Angeles, CA, United States: Inst of Elec and Elec Eng Computer Society, 2005:374-379.
[1] QU Da-yi,YANG Jing-ru,BING Qi-chun,WANG Wu-lin,ZHOU Jing-chun. Arterial traffic offset optimization based on queue characteristics at adjacent intersections [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1685-1693.
[2] LI Zhi-hui, HU Yong-li, ZHAO Yong-hua, MA Jia-lei, LI Hai-tao, ZHONG Tao, YANG Shao-hui. Locating moving pedestrian from running vehicle [J]. 吉林大学学报(工学版), 2018, 48(3): 694-703.
[3] WANG Zhan-zhong, ZHAO Li-ying, JIAO Yu-Ling, CAO Ning-bo. Social force model of pedestrian-bike mixed flow at signalized crosswalk [J]. 吉林大学学报(工学版), 2018, 48(1): 89-97.
[4] SHAO Sai, BI Jun, GUAN Wei. Electric vehicle routing problem with charging and dynamic customer demands [J]. 吉林大学学报(工学版), 2017, 47(6): 1688-1695.
[5] SUN Zong-yuan, FANG Shou-en. Hierarchical clustering algorithm of moving vehicle trajectories in entrances and exits freeway [J]. 吉林大学学报(工学版), 2017, 47(6): 1696-1702.
[6] ZHANG Zhe, JIA Li-min, QIN Yong, YUN Ting. Equalization-based feedback control model of pedestrian counter flow [J]. 吉林大学学报(工学版), 2017, 47(6): 1728-1737.
[7] LI Xian-sheng, MENG Fan-song, ZHENG Xuan-lian, REN Yuan-yuan, YAN Jia-hui. Driver's visual characteristics based on stress response [J]. 吉林大学学报(工学版), 2017, 47(5): 1403-1410.
[8] LI Zhi-hui, WANG Kun-wei, SONG Xian-min, LIU Xin-shan, SHEN Yao, LUO Rui-qi. Roundabout travel time prediction based on characteristics of lane choosing [J]. 吉林大学学报(工学版), 2017, 47(5): 1411-1419.
[9] LI Ye, WANG Wei, XING Lu, WANG Hao, DONG Chang-yin. Improving traffic efficiency of highway by integration of adaptive cruise control and variable speed limit control [J]. 吉林大学学报(工学版), 2017, 47(5): 1420-1425.
[10] WAN Ping, WU Chao-zhong, LIN Ying-zi, MA Xiao-feng. Driving anger detection based on multivariate time series features of driving behavior [J]. 吉林大学学报(工学版), 2017, 47(5): 1426-1435.
[11] JIANG Pan, YANG Jia-qi, FANG Rui-wei. Bi-level programming model for optimization of urban agglomeration comprehensive transportation corridor layout [J]. 吉林大学学报(工学版), 2017, 47(4): 1061-1067.
[12] WANG Lei, LIU Zhao, LIU Yang. Shift quality evaluation based on human response spectrum analysis [J]. 吉林大学学报(工学版), 2017, 47(3): 725-730.
[13] ZHAO Xue-yu, YANG Jia-qi, PENG Ya-mei. Competitive and cooperative relationship evolution mechanism between urban rail transit and traditional bus [J]. 吉林大学学报(工学版), 2017, 47(3): 756-764.
[14] QU Da-yi, WAN Meng-fei, LI Juan, WANG Jin-zhan, XU Xiang-hua. Offset optimization of arterial traffic based on traffic-wave theory and it control method [J]. 吉林大学学报(工学版), 2017, 47(2): 429-437.
[15] WU Wen-jing, WANG Zhan-zhong, MA Fang-wu. Simulation analysis of evolutionary game of pedestrians' group behaviors under influence of herd behavior: in case of crossing behavior [J]. 吉林大学学报(工学版), 2017, 47(1): 92-96.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd