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The surface representation in discrete form and its differential computation are important issues in computer graphics and geometric design.

0引言一般来说,曲面的一阶微分量是指曲面的切平面方向和法向量,二阶微分量是指曲面的曲率等有关量·它们作为重要的曲面信息度量指标,在计算机图形学,机器人视觉和计算机辅助设计等领域发挥了重要的作用·传统的曲面是连续形式的参数曲面和隐式曲面,其微分量的计算已经有了较完备的方法·随着激光测距扫描等三维数据采样技术和硬件设备的长足进步,以及图形工业对任意拓扑结构光滑曲面造型的需求日益迫切,离散形式的曲面———细分曲面、网格曲面和点云曲面正在逐渐成为计算机图形学和几何设计领域的新宠·于是,对这种离散形式的曲面如何估

It solves the problem that the unitary contour presentation can not correctly extract face contour in a face image which suffers from scale, rotation etc. The definition of the internal and external energy function is provided. At the same time, the global matching algorithm and local matching algorithm is given. The experiment shows that this presentation and the accompanying matching algorithm can be used to extract the face contour very well. So the image segmentation can be implemented by using it.②By analyzing the recognition principle of PCA method, we can conclude that the face images coming from different surrounding consist of different face image space. This is the essential reason that makes the generality of PCA method worse. Also, we give a measurement means to measure the distance from different face image space, so we can analyze face image space more conveniently.③We also construct various scale models and rotation pose models to detect the scale and rotating angle of face image to be recognized. The experiment results show that the detecting precision is very high. So it is good for face image feature extraction and face image representation.④Similarly, we construct local feature models of face image and utilize them to detect the local feature of face image. At the same time, we put forward a novel face image local feature detection algorithm, locating step by step. The experiment results show that this method can accurately detect the location of local face feature in a image.⑤A novel face image presentation model, dual attribute graph , is put forward. Firstly, it utilizes attribute graph to present the face image, then exact the local principal component coefficient and Gabor transform coefficient of thc pixels which corresponds to the nodes of the graph as the attribute of the nodes. This representation fully makes use of the statistical characteristic of the local face feature and utilizes Gabor transform to present the topographical structure of face image. So DAG has more general property.⑥Based on the DAG presentation, we give a DAG matching function and matching algorithm. During the design of the function and algorithm, the noise factor, e. g., lighting, scale and rotation pose are considered and tried to be eliminated. So the algorithm can give more general property.⑦A general face image recognition system is implemented. The experiment show the system can get better recognition performance under the noise surrounding of lighting, scale and rotation pose.

本文在上述研究的基础上,取得了如下主要研究成果:①构造了一个通用的人脸轮廓模型表示,解决了由于人脸图象尺度、旋转等因素而使得仅用单一轮廓表示无法正确提取人脸轮廓的问题,并给出了模型内、外能函数的定义,同时给出了模型的全局与局部匹配算法,实验表明,使用这种表示形式以及匹配算法,能够较好地提取人脸图象的轮廓,可实际用于人脸图象的分割;②深入分析了PCA方法的识别机制,得出不同成象条件下的人脸图象构成不同的人脸图象空间的结论,同时指出这也是造成PCA方法通用性较差的本质原因,并给出了不同人脸空间距离的一种度量方法,使用该度量方法能够直观地对人脸图象空间进行分析;③构造了各种尺度模板、旋转姿势模板以用于探测待识人脸图象的尺度、旋转角度,实验结果表明,探测精确度很高,从而有利于人脸图象特征提取,以及图象的有效表示;④构造了人脸图象的各局部特征模板,用于人脸图象局部特征的探测;同时提出了一种新的人脸图象局部特征探测法---逐步求精定位法,实验结果表明,使用这种方法能够精确地得到人脸图象各局部特征的位置;⑤提出了一种新的人脸图象表示法---双属性图表示法;利用属性图来表示人脸图象,并提取图节点对应图象位置的局部主成分特征系数以及Gabor变换系数作为图节点的属性,这种表示方法充分利用了人脸图象的局部特征的统计特性,并且使用Gabor变换来反映人脸图象的拓扑结构,从而使得双属性图表示法具有较强的通用性;⑥在双属性图表示的基础上,给出双属性图匹配函数及匹配算法,在函数及算法设计过程中,考虑并解决了光照、尺度、旋转姿势变化等因素对人脸图象识别的影响,使得匹配算法具有较强的通用性;⑦设计并实现了一个通用的人脸图象识别系统,实验结果表明,该系统在图象光照、尺度、旋转姿势情况下,得到了较好的识别效果。

Then, the first and second fundamental forms, Gaussian curvature and mean curvature of the surfaces are directly calculated according to the principles of differential geometry.

首先,根据微分几何中的基本知识,得到了该种度量形式下的平移曲面的第一、第二基本形式以及高斯曲率和平均曲率;然后,主要利用高斯曲率和平均曲率之间的线性关系和平方关系,得到了这类平移曲面的分类定理。

A new metric form is chosen to study the Weingarten translation surfaces which are translating in the two null directions in a pseudo orthogonal frame.

在伪正交标架下,选取一种新的度量形式,对沿两个类光方向平移的平移Weingarten曲而进行了研究。

Metric form.

度量形式

Let x: M→S(superscript n+1)(n≥3) be a hypersurface in the (n+1)-dimensional unit sphere without umbilic points. Denote the Mbius metric, the Mbius form, the Blaschke form and the Mbius second fundamental form of x by G,Ф, A and B, repcectively, which are Mbius invariants in Mbius differential geometry.

设x: M→S(上标 n+1)(n≥3)是n+1-维单位球中的无脐点超曲面,Mbius不变量G,Ф,A和B分别表示x的Mbius度量,Mbius形式,Blaschke形式和Mbius第二基本形式。

By applying these two tools,we mainly discuss the problems as follows:1 Perturbation identities for the generalized polar decomposition:By applying singular value decomposition, we study the perturbation bounds of the generalized polar decomposition under unitary invariant norms when A is perturbed by addition or multiplication,respectively and give our bounds in identities.2 A class of new unitary invariant metrics: This paper generalized a class of new unitarily invariant metrics and give the upper-bounds and lower-bounds by C-S decomposition.

利用这两个强有力的工具,本文主要讨论了如下问题:1 矩阵广义极分解的扰动等式:利用奇异值分解,本文分别讨论了加法扰动和乘法扰动下矩阵广义极分解在任意酉不变范数下的扰动界,并首次以恒等式的形式给出了酉极因子和半正定因子的扰动界。2 一类新的酉不变度量:本文推广了文[22] 中的结论,定义了一类新的酉不变度量。

The projective geometry is geometry of non-measured form.

射影几何是非度量形式的几何。

The research showed that the non- quadratic form distance metrics perform as well as the quadratic form metrics.

研究表明,非二次形式的距离度量与二次形式的距离度量一样有良好的性能。

The fifth chapter argues that differences exist among the gradability of different types of reduplicatively descriptive adjectives, even among the same reduplicative forms.

第五章中认为不仅不同类型的重叠式状态形容词之间存在着程度量等级差别,而且同一重叠形式之内也存在着程度量等级的差别。

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Singer Leona Lewis and former Led Zeppelin guitarist Jimmy Page emerged as the bus transformed into a grass-covered carnival float, and the pair combined for a rendition of "Whole Lotta Love".

歌手leona刘易斯和前率领的飞艇的吉他手吉米页出现巴士转化为基层所涵盖的嘉年华花车,和一双合并为一移交&整个lotta爱&。

This is Kate, and that's Erin.

这是凯特,那个是爱朗。

Articulate the aims, objectives and key aspects of a strategic business plan.

明确的宗旨,目标和重点战略业务计划。