The Vehicle Capture Algorithms of Virtual Bayonet System

Article Preview

Abstract:

With the introduction of a large number of high-definition cameras in safe city construction, it is important to analyze the data of high-definition video camera which densely distributed as the entry point to design a reuse-based high-definition video capture function monitoring and to achieve a virtual mount system. Virtual card mouth research vehicle target recognition technology has become the key technology of virtual mount system construction. This system do video vehicle detection algorithm to realize the vehicle by a bayonet analysis and extraction of moving vehicles can achieve urban networking dispatched for traffic accident and criminal cases to provide effective security information and means to solve the case.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

3832-3835

Citation:

Online since:

November 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Zhu Liying, Liang Chen moving target surveillance video retrieval method [D] Based Computer Applications and Software, 2011, 12: 28-12.

Google Scholar

[2] Tang Zhen, Huang Ye Liang, Yang Hua. Definition bayonet intelligent information security identification system and application [J], Television Technology, 2012, 36 (14).

Google Scholar

[3] Han Bohyung, Comaniciu D, Ying Zhu, et al. Sequential kernel density approximation and its application to real-time visual tracking [J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2008, 30(7): 1186-1197.

DOI: 10.1109/tpami.2007.70771

Google Scholar

[4] Kalal Z, Mikolajczyk K, Matas J. Tracking learning detection[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2012, 34(7): 1409-1422.

DOI: 10.1109/tpami.2011.239

Google Scholar

[5] Qi Meibin, fresh Ke, Jiang Jianguo contrast distortion parameters based on traffic statistics algorithm [J], Hefei University of Technology: Natural Science News, 2010, 33 (12): 1815-1823.

Google Scholar

[6] Zhang Haiqing, LiHouqiang Target tracking based on Monte Carlo method [J] China Journal of Image and Graphics, 2008, 13 (5): 937-938.

Google Scholar

[7] Xie Fengying VC ++ Digital Image Processing [M] Beijing: Electronic Industry Press, 2008, 9.

Google Scholar