智能运输系统初探

考察智能运输系统ＩＴＳ，特别是其中的自动高速公路系统ＡＨＳ。着重讨论ＡＨＳ的目标，配置，体系结构和功能分解，分析其中的高层网络优化，中层多自主体调度和底层自动车辆控制等问题。     

从头到脚完美Word文档布局

页眉和页脚是分别位于页面的顶部和底部并独立于文档的部分，在其中不仅可以包括“自动图文集”，页码等信息，还能将更多有趣的应用运用其中。     

三大门户股价悬念

三大门户因股价暴涨再次引人注目，其中搜狐和网易的股价已经离两年前的高峰期相去不远。和上次不同的是，此次的上涨有其优良的业绩做支撑，其中，广告、短信和游戏功不可没，但未来三大业务能否支撑高高在上的股价，却仍是一个未知数。     

用RivaTuner调试NVIDIA显卡

NVIDIA的显卡占有家用市场相当大的份额，所以针对它的调试工具相当多，其中不乏佼佼者，RivaTune蹴是其中一个。能在众多的竞争者中脱颖而出，RivaTuner靠的是小巧的体积和强大的集成功能。     

浅谈C#多版本构造函数的设计

学习面向对象程序设计，有很多难点和重点需要突破。其中构造函数就是难点和重点之一。而诸如虚拟构造函数，构造函数的重载等又是构造函数中的难点。学习构造函数重载的语法相当容易，但实际应用起来却有着不小的困难。我在实际编程中便遇到了一些，并且通过看书和思考得到了解决，其中心得不小，写出来希望     

Amazon开发类图书金秋观察

当我打开Amazon的Bestsellers页面，浏览Computers ＆ Intemet下的排行情况时，大失所望，因为其中有太多的老面孔，缺少“激扬文字”的新热点。而且，随着Web2．0和AJAX概念热度的减弱，国内技术图书市场也处在没有热点的平淡期。但是在我仔细翻看了其中Databases和Programming子项排行，     

用Borland C＋＋Builder实现语音聊天

说起UP或RUP，一般都会津津乐道其中的用例驱动、架构为中心、迭代和增量的原则。但实践中往往难度不在一个虚的“过程”，而是其中的技能。     

性能测试

《个人电脑》联合新浪网、IT168举办的大型专题评测得到了各笔记本电脑厂商的大力支持，在本月，我们对其中的超便携笔记本电脑和消费类笔记本电脑做了一个总结。本次专题中涉及到的产品共达19款，其中超便携笔记本电脑11款，消费类笔记本电脑8款，其中既有《个人电脑》已经测试过的产品，也有厂商即将推出的新品。我们将它们一并邀请到实验室时行了评测。     

莫让开心变折磨

自从开心网、校内网等SNS社区推出种菜、赛车、养狗、奴隶买卖等虚拟游戏后，不少白领沉迷其中。为了迎合用户，这些个小游戏的制作普遍十分精良，游戏规则简单明了又趣味十足，其中影响和成瘾率最高的当属“开心农场”类的种菜游戏。     

客厅家电的好邻居

家，是众多“元素”的聚合体，当然，人是其中绝对的主角。除此之外，家电和家具则是其中重要的组成部分。尤其在影音家电较为集中的客厅或者视听室内，电器和家具更是扮演着不可或缺的主力角色。或许你是乔迁新居，也或者你正筹划着为家来一次更新换代。那么，不妨来这里为你的客厅电器找到最合称的好邻居。     

MIRA-3D: A three-dimensional graphical extension of pascal

MIRA-3D is a three-dimensional graphical extension of Pascal based on abstract graphical types. The user may define and manipulate complex 3D objects, as well as image transformations. Viewing transformations and attributes are compatible with the ACM GSPC Core System. A large set of graphical primitives are available and the paper discusses the most important ones. Portability has also been an important criterion in implementation.     

Continuous Generalized Procrustes analysis

Two-dimensional shape models have been successfully applied to solve many problems in computer vision, such as object tracking, recognition, and segmentation. Typically, 2D shape models are learned from a discrete set of image landmarks (corresponding to projection of 3D points of an object), after applying Generalized Procustes Analysis (GPA) to remove 2D rigid transformations. However, the standard GPA process suffers from three main limitations. Firstly, the 2D training samples do not necessarily cover a uniform sampling of all the 3D transformations of an object. This can bias the estimate of the shape model. Secondly, it can be computationally expensive to learn the shape model by sampling 3D transformations. Thirdly, standard GPA methods use only one reference shape, which can might be insufficient to capture large structural variability of some objects.To address these drawbacks, this paper proposes continuous generalized Procrustes analysis (CGPA). CGPA uses a continuous formulation that avoids the need to generate 2D projections from all the rigid 3D transformations. It builds an efficient (in space and time) non-biased 2D shape model from a set of 3D model of objects. A major challenge in CGPA is the need to integrate over the space of 3D rotations, especially when the rotations are parameterized with Euler angles. To address this problem, we introduce the use of the Haar measure. Finally, we extended CGPA to incorporate several reference shapes. Experimental results on synthetic and real experiments show the benefits of CGPA over GPA.     

A spring–mass model-based approach for warping cloth patterns on 3D objects

This paper presents a general method for transformations of an object between 2D and 3D which can be used efficiently in computer-aided garment design. A uniform triangular spring–mass-based deformable model is employed. Both 2D-to-3D and 3D-to-2D transformations can be implemented in the same model. An efficient collision detection method is also discussed. © 1998 John Wiley & Sons, Ltd.     

On the learning machine for three dimensional mapping

In this paper, we investigate the neural network with three-dimensional parameters for applications like 3D image processing, interpretation of 3D transformations, and 3D object motion. A 3D vector represents a point in the 3D space, and an object might be represented with a set of these points. Thus, it is desirable to have a 3D vector-valued neural network, which deals with three signals as one cluster. In such a neural network, 3D signals are flowing through a network and are the unit of learning. This article also deals with a related 3D back-propagation (3D-BP) learning algorithm, which is an extension of conventional back-propagation algorithm in the single dimension. 3D-BP has an inherent ability to learn and generalize the 3D motion. The computational experiments presented in this paper evaluate the performance of considered learning machine in generalization of 3D transformations and 3D pattern recognition.     

基于三维网格物体的鲁棒性盲水印方案

提出了一种基于3D网格物体的鲁棒性盲水印方案。先将3D物体模型转换到仿射不变空间,然后把顶点坐标转换到球面坐标,利用球面坐标来嵌入水印。由于在仿射不变空间下,3D物体模型不受平移、旋转和比例变换的影响,故该水印方案对于此类变化具有很强的鲁棒性。试验结果也证明了这一点,且该水印具有良好的不可见性。     

True multi-image alignment and its application to mosaicing andlens distortion correction

Multiple images of a scene are related through 2D/3D view transformations and linear and nonlinear camera transformations. We present an algorithm for true multi-image alignment that does not rely on the measurements of a reference image being distortion free. The algorithm is developed to specifically align and mosaic images using parametric transformations in the presence of lens distortion. When lens distortion is present, none of the images can be assumed to be ideal. In our formulation, all the images are modeled as intensity measurements represented in their respective coordinate systems, each of which is related to an ideal coordinate system through an interior camera transformation and an exterior view transformation. The goal of the accompanying algorithm is to compute an image in the ideal coordinate system while solving for the transformations that relate the ideal system with each of the data images. Key advantages of the technique presented in this paper are: (i) no reliance on one distortion free image, (ii) ability to register images and compute coordinate transformations even when the multiple images are of an extended scene with no overlap between the first and last frame of the sequence, and (iii) ability to handle linear and nonlinear transformations within the same framework. Results of applying the algorithm are presented for the correction of lens distortion, and creation of video mosaics     

Transformations of normal and inverted function tables

We develop a theory of function tables, similar to, and inspired by, that given in the work of D. Parnas. We consider, in particular, two classes of function tables: normal and inverted. We study effective transformations between tables of these two classes, as well as transformations which change the dimension of a table. We also consider the interrelationship between these three types of transformation.     

基于小波变换的三维网格物体盲水印方案

提出了一种基于小波变换的3D网格物体鲁棒性盲水印方案.首先将3D物体模型转换到仿射不变空间,抽取三维物体重心到顶点的距离生成一个一维的离散信号;将该离散信号进行小波变换,改变其高频系数以嵌入水印,然后经过小波逆变换生成带水印的3D物体模型.在仿射不变空间下,实现了3D物体模型对平移、旋转、比例变换的鲁棒性,采用小波变换使3D模型具有很强的水印不可见性以及一定的噪声鲁棒性.试验结果表明,该方法不仅对于旋转、平移、比例变换具有很强的鲁棒性,而且具有良好的水印不可见性.     

AN EMPIRICAL EVALUATION OF INTEREST POINT DETECTORS

Image interest point extraction and matching across images is a commonplace task in computer vision–based applications, across widely diverse domains, such as 3D reconstruction, augmented reality, or tracking. We present an empirical evaluation of state-of-the-art interest point detection algorithms measuring several parameters, such as efficiency, robustness to image domain geometric transformations—that is, similarity—affine or projective transformations, as well as invariance to photometric transformations such as light intensity or image noise.