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Method and apparatus for moving object detection using principal component analysis based radial basis function network

机译:使用基于主成分分析的径向基函数网络进行运动物体检测的方法和装置

摘要

A method for moving object detection based on a Principal Component Analysis-based Radial Basis Function network (PCA-based RBF network) includes the following steps. A sequence of incoming frames of a fixed location delivered over a network are received. A plurality of Eigen-patterns are generated from the sequence of incoming frames based on a Principal Component Analysis (PCA) model. A background model is constructed from the sequence of incoming frames based on a Radial Basis Function (RBF) network model. A current incoming frame is received and divided into a plurality of current incoming blocks. Each of the current incoming blocks is classified as either a background block or a moving object block according to the Eigen-patterns. Whether a current incoming pixel of the moving object blocks among the current incoming blocks is a moving object pixel or a background pixel is determined according to the background model.
机译:基于基于主成分分析的径向基函数网络(基于PCA的RBF网络)的运动对象检测方法包括以下步骤。接收通过网络传送的固定位置的一系列传入帧。基于主成分分析(PCA)模型,从传入帧的序列中生成多个特征模式。基于径向基函数(RBF)网络模型,根据传入帧的序列构建背景模型。接收当前输入帧并将其划分为多个当前输入块。根据本征模式,每个当前进入的块被分类为背景块或运动对象块。根据背景模型确定当前进入块中的运动对象块的当前进入像素是运动对象像素还是背景像素。

著录项

  • 公开/公告号US9349193B2

    专利类型

  • 公开/公告日2016-05-24

    原文格式PDF

  • 申请/专利权人 NATIONAL TAIPEI UNIVERSITY OF TECHNOLOGY;

    申请/专利号US201414231637

  • 发明设计人 SHIH-CHIA HUANG;BO-HAO CHEN;

    申请日2014-03-31

  • 分类号G06T7/00;G06T7/20;G06K9/00;G06K9/62;G06K9/32;

  • 国家 US

  • 入库时间 2022-08-21 14:30:31

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