三维扩散模型在视频行为识别中的应用  

Research of video behavior identification based on three-dimensional diffusion model

作　　者：雷金娥[1] 

机构地区：[1]南昌工程学院计算机与科学技术系,南昌330099

出　　处：《计算机工程与应用》2009年第32期156-158,共3页Computer Engineering and Applications

基　　金：南昌工程学院青年基金-科技项目(No.2006KJ029)

摘　　要：内容识别是视频和图像分析的主要目的之一,由于视频内容的复杂性,视频内容自动分析和识别并不容易实现,目前没有通用的视频行为识别方法和理论。三维各向异性扩散方程可以实现视频信号的多尺度分析,方便行为特征的描述和提取。通过多尺度分析结合支持向量机分类,可以系统地解决视频对象识别、运动识别和行为识别等一系列问题。实验表明,即使在样本行为特征未知的情况下,通过机器学习,也可以实现对视频行为的识别,说明这种行为识别方法可以用于任意已知样本的行为识别问题。Content recognition is one main purpose of video and image analysis,however,due to the complexity of video content, it is hard to realize automatic analysis and identification,and there are no universal method and theories of identification of video at present.3D anisotropic diffusion equations can achieve video signals analysis in the multi-scale to facilitate the description and extraction of characteristics.It can solve the video object recognition,activity recognition and behavior recognition etc by the multi-scale analysis and SVM（Support Vector Machines） classification system.The experiments show that the new method can identify video behavior even in the circumstances where sample characteristics remain unknown,which prove that the method can be used to identify any of the known samples through machine learning.

关 键 词：视频 行为识别 三维扩散模型 支持向量机 

分 类 号：TP301.4[自动化与计算机技术—计算机系统结构]