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基于模糊聚类神经网络的镜头突变检测算法
引用本文:沈淑娟,姜建国,曹建春.基于模糊聚类神经网络的镜头突变检测算法[J].计算机工程与设计,2004,25(9):1612-1614.
作者姓名:沈淑娟  姜建国  曹建春
作者单位:西安电子科技大学,计算机学院,陕西,西安,710071
摘    要:讨论了采用无监督的模糊竞争学习算法,并结合自组织竞争网络构成的一种新型模糊聚类神经网络模型,提出了一种基于该网络模型的镜头突变检测算法。该算法通过对线性特征空间进行由粗到细的两步模糊聚类实现镜头突变的检测。实验结果表明该算法是可行和有效的。

关 键 词:竞争学习算法  模糊聚类  竞争网络  线性特征  网络模型  镜头  自组织  测算法  类神经网络  监督
文章编号:1000-7024(2004)09-1612-03

Algorithm of abrupt shot boundary detection based on fuzzy clustering neural network
SHEN Shu-juan,JIANG Jian-guo,CAO Jian-chun College of Computer,Xidian University,Xi'an ,China.Algorithm of abrupt shot boundary detection based on fuzzy clustering neural network[J].Computer Engineering and Design,2004,25(9):1612-1614.
Authors:SHEN Shu-juan  JIANG Jian-guo  CAO Jian-chun College of Computer  Xidian University  Xi'an  China
Affiliation:SHEN Shu-juan,JIANG Jian-guo,CAO Jian-chun College of Computer,Xidian University,Xi'an 710071,China
Abstract:A novel model of fuzzy clustering neural network is discussed, which synthesizes unsupervised fuzzy competitive learning algorithm and self-organizing competitive network. Based on this model, an algorithm of video shot boundary detection is presented. This algorithm performs the detection by a two-stage clustering on the linear feature space. The experimental results obtained demonstrate that the algorithm is feasible and efficient.
Keywords:fuzzy clustering  neural network  competitive learning algorithm  abrupt shot boundary detection
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