Intrusion Detection and Tracking at Railway Crossing-Reference-Cited by-同舟云学术

Intrusion Detection and Tracking at Railway Crossing

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing - AIAM 2019
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Author:

Cai Naxin¹,Chen Houjin¹,Li Yanfeng¹,Peng Yahui¹

Affiliation:

1. School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

ACM Press

Reference13 articles.

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2. S. C. Mok, I. Savage (2005). Why Has Safety Improved at Rail-Highway Grade Crossings? Risk Analysis: An International Journal, 25, 867--881.

3. O. Barnich, M. Van Droogenbroeck (2010). ViBe: A universal background subtraction algorithm for video sequences. IEEE Transactions on Image processing, 20, 1709--1724.

4. C. Stauffer, W. E. L. Grimson (1999). Adaptive background mixture models for real-time tracking. Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149). IEEE, 2, 246--252.

5. Á. Bayona, J. C. SanMiguel, J. M. Martínez (2009). Comparative evaluation of stationary foreground object detection algorithms based on background subtraction techniques. 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance. IEEE, 25--30.

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