Abstract
In this paper, a novel approach of data field is proposed to discover the action pattern of real-time person tracking, and potential function is presented to find out the power of a person with suspicious action. Firstly, a data field on the first feature is used to find the individual attributes, associated with the velocity, direction changing frequency and appearance frequency respectively. Secondly, the common characteristic of each attribute is obtained by the data field on the main feature from the data field created before. Thirdly, the weighted Euclidean distance classifier is used to identify whether a person is a suspect or not. Finally, the results of the experiment show that the proposed way is feasible and effective in action mining.
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© 2008 Springer-Verlag Berlin Heidelberg
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Wang, S., Wu, J., Cheng, F., Jin, H. (2008). Real-Time Person Tracking Based on Data Field. In: Tang, C., Ling, C.X., Zhou, X., Cercone, N.J., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2008. Lecture Notes in Computer Science(), vol 5139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88192-6_80
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DOI: https://doi.org/10.1007/978-3-540-88192-6_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88191-9
Online ISBN: 978-3-540-88192-6
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