Abstract
This paper presents a model OMDB for mining the region information of non-rigid foreground object in video flow with dynamic background. The model constructs RDM algorithm and optimize the strategy of region matching using Q-learning to obtain better motion information of regions. Moreover, OMDB utilizes NEA algorithm to detect and merge gradually object regions of foreground based on the characteristics that there is motion difference between foreground and background and the regions of an object maintain integrality during moving. Experimental results on extracting region information of foreground object and tracking the object are presented to demonstrate the efficacy of the proposed model.
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© 2005 Springer-Verlag Berlin Heidelberg
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Zeng, C., Cao, J., Fang, Y., Du, P. (2005). Data Mining Based on Objects in Video Flow with Dynamic Background. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_46
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DOI: https://doi.org/10.1007/11527503_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27894-8
Online ISBN: 978-3-540-31877-4
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