Abstract
Understanding human and object behaviors in video surveillance systems is an important factor and particular interest as far as public security is concerned. In this paper, we propose a novel method for object classification and tracking processes. It has been well recognized that the two processes play important roles in video surveillance system to make them intelligent. The proposed system is able to detect and classify human and non-human in different weather conditions. The system is capable of correctly tracking multiple objects despite occlusions and object interactions. Some experimental results are presented by using self-collected data.
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Acknowledgment
This work was supported by JSPS KAKENHI Grant Number JP15K14844.
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Zin, T.T., Yamada, K. (2017). An Automatic Target Tracking System Based on Local and Global Features. In: Pan, JS., Lin, JW., Wang, CH., Jiang, X. (eds) Genetic and Evolutionary Computing. ICGEC 2016. Advances in Intelligent Systems and Computing, vol 536. Springer, Cham. https://doi.org/10.1007/978-3-319-48490-7_30
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DOI: https://doi.org/10.1007/978-3-319-48490-7_30
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