Abstract
A general method for traffic video surveillance task involves foreground detecting and moving objects’ tracking. The Gaussian mixture model is generally used in detecting foreground and the Kalman filter is used in multi-objects tracking. This paper has implemented a multi-objects tracking system using DM3730 development board as the hardware platform, which is powerful at image processing and analysis. This paper will adopt an Open Computer Vision library (OpenCV) to efficiently implement the overall system. The OpenCV library with a large amount of optimized algorithms in computer vision and machine learning will facilitate the realization of the system. The testing results demonstrate the effectiveness of the system through tracking of vehicles.
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References
Wang, X., Ma, X., Grimson, W.E.L.: Unsupervised activity perception in crowded and complicated scenes using hierarchical bayesian models. TPAMI 31(3), 539–555 (2009)
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Proceedings of IEEE CVPR, pp. 246–252, June 1999
Faragher, R.: Understanding the basis of the Kalman filter via a simple and intuitive derivation. IEEE Sig. Process. Mag. 29(5), 128–132 (2012)
Varfolomieiev, A., Lysenko, O.: An improved algorithm of median flow for visual object tracking and its implementation on TI OMAP. In: Proceedings of EDERC, pp. 261–265, September 2012
Sakai, Y., Oda, T., Ikeda, M., Barolli, L.: An object tracking system based on SIFT and SURF feature extraction methods. In: INWC, pp. 561–565, September 2015
Li, D., Liang, B., Zhang, W.: Real-time moving vehicle detection, tracking, and counting system implemented with OpenCV. In: Proceedings of IEEE ICIST, pp. 631–634, April 2014
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, X., Dong, H. (2018). Realization of Traffic Video Surveillance on DM3730 Chip. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_44
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DOI: https://doi.org/10.1007/978-3-319-73447-7_44
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