Data mining based on objects in video flow with dynamic background

Authors:
Cheng Zeng;JiaHeng Cao;Ying Fang;Pei Du
Affiliations:
Computer School, Wuhan University, Wuhan, P.R. China;Computer School, Wuhan University, Wuhan, P.R. China;Computer School, Wuhan University, Wuhan, P.R. China;Computer School, Wuhan University, Wuhan, P.R. China
Venue:
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
Year:
2005

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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.