Abstract
Since limitations have been encountered in the achievement of the traditional targets tracking algorithms, a novel tracking method based on local block-graphs targets matching is proposed. Car flow tracking is applied to prove the effectiveness of the method. First, the images containing the targets are captured by the video frames to get the targets block-graphs. Second, the block-graphs can be used to achieve targets matching, and the detection process can be achieved by targets matching to get the optimal targets set. Finally, the targets set can be used to achieve the minimum deviation forecasting of all frames, and the targets tracking can be achieved. A junction video is selected as the experimental data, and a large number of experiments have been done. The results show that the proposed method not only has a great effect to track cars, but also has a better detection rate and tracking accuracy. The car flow statistics can be completed effectively.
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Acknowledgments
The authors would like to thank for the supports from the National Natural Science Foundation of China (61272253) and the Ministry of Housing and Urban-Rural Development, China (2010-K9-22).
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Liu, J., Gong, Z., Wang, X., Gao, E., Xu, Z. (2014). Tracking and Statistics Method Based on LBTM for Traffic Car Flow. In: Liu, L., Zhu, Q., Cheng, L., Wang, Y., Zhao, D. (eds) Applied Methods and Techniques for Mechatronic Systems. Lecture Notes in Control and Information Sciences, vol 452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36385-6_14
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DOI: https://doi.org/10.1007/978-3-642-36385-6_14
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