搜狗做题网英语翻译Figure-ground segmentation is the process of separating
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英语翻译
Figure-ground segmentation is the process of separating the objects of interest(humans) from the rest of the image(the background).Methods for figure-ground segmention are often applied as the first step in many systems and therefore a crucial process.Recent advances are mostly a result of expanding existing methods.We categorize these methods in accordance with the type of image measurements the segmentation is based on:motion,appearance.shape,or depth data.Before describing these we first review recent advances in background subtraction as this has become the initial step in many tracking algorithms.
Background subtraction
Up until the late 90s background subtraction was known as a powerful preprocessing step but only in controlled indoor environments.In 1998,Stauffer and Grimson presented the idea of representing each pixel by a mixture of Gaussians during run-time.This allows background subtraction to be used in outdoor environments.Normally the updating was done recursively,which can model slow changes in a scene,but not rapid changes like clouds.The method by Stauffer and Grimson has today become the standard of advances have been seen which can be divided into background representation,classification.background updating,and background initialization.
Figure-ground segmentation is the process of separating the objects of interest(humans) from the rest of the image(the background).Methods for figure-ground segmention are often applied as the first step in many systems and therefore a crucial process.Recent advances are mostly a result of expanding existing methods.We categorize these methods in accordance with the type of image measurements the segmentation is based on:motion,appearance.shape,or depth data.Before describing these we first review recent advances in background subtraction as this has become the initial step in many tracking algorithms.
Background subtraction
Up until the late 90s background subtraction was known as a powerful preprocessing step but only in controlled indoor environments.In 1998,Stauffer and Grimson presented the idea of representing each pixel by a mixture of Gaussians during run-time.This allows background subtraction to be used in outdoor environments.Normally the updating was done recursively,which can model slow changes in a scene,but not rapid changes like clouds.The method by Stauffer and Grimson has today become the standard of advances have been seen which can be divided into background representation,classification.background updating,and background initialization.
身材- 地面的分割是分开来自图像 (背景) 的其它部分的重要物体的程序.为身材- 地面的 segmention 的方法时常被应用如许多系统的第一个步骤因此一个决定性的程序.最近的进步大概是扩张现有的方法结果.我们符合分割为基础的图像测量的类型分类这些方法:运动,appearance.shape 或深度数据.当这已经变得追踪运算法则的多数开始的步骤时候,在首先描述这些我们之前检讨背景减少的最近进步.
背景减少
提高,直到 90 年代后期背景减少即是一个有力的预加工步骤除了只有在受约束的户内环境中之外.在 1998 年,Stauffer 和 Grimson 呈现了在奔跑期间表现一个高斯的混合每个图素的主意-时间.这允许背景减少被用于户外的环境.正常地那更新回归地被做,哪一能在现场中慢地做模型变化,但是不是迅速的像云变化.Stauffer 和 Grimson 的方法今天已经变得进步的标准能被区分为背景表现,classification.background 更新和背景设定初值被见到.
你有些单词有问题.
背景减少
提高,直到 90 年代后期背景减少即是一个有力的预加工步骤除了只有在受约束的户内环境中之外.在 1998 年,Stauffer 和 Grimson 呈现了在奔跑期间表现一个高斯的混合每个图素的主意-时间.这允许背景减少被用于户外的环境.正常地那更新回归地被做,哪一能在现场中慢地做模型变化,但是不是迅速的像云变化.Stauffer 和 Grimson 的方法今天已经变得进步的标准能被区分为背景表现,classification.background 更新和背景设定初值被见到.
你有些单词有问题.
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