matlab分时代码-DMD_Foreground_Detection:动态模式分解(DMD)用于视频中的前景检测-MATLAB

上传者: 38606019 | 上传时间: 2021-09-27 14:14:04 | 文件大小: 488KB | 文件类型: ZIP
matlab分时代码动态模式分解(DMD)用于视频中的前景检测 由J.Barhydt 1 华盛顿大学华盛顿州西雅图市98195 概述: 动态模式分解(DMD)已经成为分解非线性系统以对基本动力学建模的不可思议的价值工具。 DMD提供的模式集与其他降维方法不同,例如奇异值分解(SVD)和主成分分析(PCA),因为DMD提供了基础模式的振荡时间分辨率,因此每个模式都包含时空信息。 振荡行为在许多物理系统中均会出现,从而使DMD分析具有更大的“捕获”这些动力学的能力。 在本文中,假设背景比移动和变化的前景具有更多的固定时间动态,则使用DMD将视频流中的前景与背景分离。 1-此报告使用扩展的Yale Faces B数据库: 简介与概述 ================================= 前景检测是人类(以及许多动物)可以很自然地完成的任务。 看过电影《侏罗纪公园》的任何人都可以证明霸王龙检测前景的能力很弱。 从某种意义上说,DMD方法的功能将非常相似。 通过将视频分解为基本的时空模式,DMD方法允许人们“挑选”具有最低振荡频率的模式,从而构成低等级的“背景”。 在具有静态背景的

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