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图像的纹理分析方法(从图像、图形融合的思想出发 ，介绍了基于图像分析的表面形状恢复及纹理
三维特征获取方法，并将其应用于图形建模和纹理映射．首先利用不同视点下的遮挡
边缘序列，并结合其它视觉信息的分析，获取了表面点的三维几何坐标，实现了基于
图像分析的表面形状绘制．接着利用阴影分析方法，提取纹理图像的表面起伏特征，
将该特征结合像素点的颜色属性，进行图形纹理映射，实现了基于图像特征分析的图
形纹理生成．实验结果证明了图像、图形融合思路的可行性和有效性及图像、图形融
合方法
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This paper describes a vision based pedestrian detection and tracking system which is able to count people in very crowded situations like escalator entrances in underground stations. The proposed system uses motion to compute regions of interest and
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鲁棒性 在从纹理回复形状的时候要求系统有好的鲁棒特性-Robust back in shape from the texture when the request has good robustness properties of system
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表面缺损检测对保证产品的使用性能、完整性和安全性具有重要意义 本文将表面
缺损类型总结为结构缺损、几何缺损、颜色缺损和纹理缺损等几类，并进行特征分析。在此基础上，从基于灰度特征、形态特征、色度特征和纹理特征等几方面对表面缺损的图像检测方法进行综-Surface defect detection products to ensure the use of performance, integrity and security will be of great significance to t
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ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。
基本思想：
在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。
-Descr iption This is an example of the basic Active Shape Model (ASM) as introduced by Coot
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从互联网上找到的一个关于颜色，纹理，形状提取图像特征的源码-color texture shape detection,source and doc from the web
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The objective of this paper is to provide an overview of the current state of the art from both methodologicaland experimental perspectives. The first part of the paper consists of a survey. We cover the main components of a pedestrian detection syst
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In substance, Computer Graphics is a process of transformation from the 3D model object in the form of information
geometric shape, pose information, color, texture, and lighting into a 2D image
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基于纹理和边缘方向特征融合的目标跟踪程序代码，是基于mean shift框架的-This paper proposes a powerful and robust local descr iptor,called textureorientation
descr iptor(TOD). TOD consists of two components: texture and
orientation. Considering that the human shape shows more s
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The 3-D Morphable Model was
introduced as a generative model to p redictthe appearances o f
an individual while using a statistical prior on shape and
texture allowin g its parameters to be estimated from single
image. Based on these new unde
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