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Initial Object Segmentation for Video Object Plane Generation Using Cellular Neural Networks

Initial Object Segmentation for Video Object Plane Generation Using Cellular Neural Networks
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摘要 MPEG 4 is a basic tool for interactivity and manipulation of video sequences. Video object segmentation is a key issue in defining the content of any video sequence, which is often divided into two steps: initial object segmentation and object tracking. In this paper, an initial object segmentation method for video object plane(VOP) generation using color information is proposed. Based on 3 by 3 linear templates, a cellular neural network (CNN) is used to implemented object segmentation. The Experimental results are presented to verify the efficiency and robustness of this approach. MPEG 4 is a basic tool for interactivity and manipulation of video sequences. Video object segmentation is a key issue in defining the content of any video sequence, which is often divided into two steps: initial object segmentation and object tracking. In this paper, an initial object segmentation method for video object plane(VOP) generation using color information is proposed. Based on 3 by 3 linear templates, a cellular neural network (CNN) is used to implemented object segmentation. The Experimental results are presented to verify the efficiency and robustness of this approach.
出处 《Journal of Shanghai University(English Edition)》 CAS 2003年第2期168-172,共5页 上海大学学报(英文版)
基金 ProjectsupportedbytheNationalNatureScienceFoundationofChina(GrantNo .60 172 0 2 0 )
关键词 video object plane(VOP) cellular neural networks(CNN) templates. video object plane(VOP), cellular neural networks(CNN), templates.
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