特征融合和聚类核函数平滑采样优化的粒子滤波目标跟踪方法

针对复杂场景下的目标跟踪问题,提出了一种改进的粒子滤波目标跟踪方法。利用背景加权后的联合直方图描述目标灰度和梯度特征信息,在粒子滤波算法的框架下,设计了一种自适应特征融合观测模型来适应场景的不断变化;同时针对传统粒子滤波算法存在的粒子退化问题,提出了一种基于聚类核函数平滑采样的方法。理论仿真和实际场景的实验结果表明,该算法适应性更强,精度更高,能有效跟踪复杂场景下的运动目标。     

基于Tikhonov正则的图像盲复原算法

图像在获取、传输及保存的过程中,很多因素会导致图像质量退化,图像模糊是图像质量退化的一种常见表现。基于全变差(TV)的图像复原Chan模型虽然能较好地刻画导致图像质量退化的模糊核,但该模型的图像复原结果严重依赖于参数的选取。针对Chan模型对参数敏感的问题,在该模型中引入模糊核的Tikhonov正则,提出新的盲去糊模型,并证明新的盲复原模型解的存在性。另外,采用由粗到精的多层图像金字塔策略,构造模糊核的初始值,再结合交替极小化(alternating minimization, AM)方法,设计基于初始模糊核的快速算法求解所提模型。数值实验结果表明：所提模型与其他正则化模型相比,在不需要模糊核动态阈值约束的前提下,不仅能得到高质量的图像复原结果,而且对参数有较好的鲁棒性。     

一种基于稀疏系数匹配学习的图像去雾算法

针对现有基于先验假设的图像去雾算法无法普适性求解问题,提出一种基于稀疏系数匹配学习的图像去雾算法.该算法从图像复原角度出发,将雾天退化模型的求解转换为基于数据库的稀疏系数匹配.之后,从图像增强角度着手,将图像高亮区域对比度恢复量化为反馈迭代问题,进而有效提升图像的视觉效果.实验结果表明,所提出的算法在获得较好去雾结果的同时能够有效提升图像细节和对比度,并具有较强的适用性.     

基于调和模型的快速神经网络图像复原算法

针对传统神经网络图像复原算法在复原过程中模糊图像边缘,收敛速度慢等不足,提出一种基于调和模型的快速神经网络图像复原算法.在该算法中,图像复原模型的正则化项采用调和模型,并在每次网络状态更新时引入最陡下降方法,使得网络能量迅速减小.实验表明,提出的算法能够很好复原图像的边缘特征,并具有快速收敛等优点.     

基于边缘先验模型的运动去模糊

从单幅运动模糊图像复原出清晰的图像,一直是数字图像处理领域中富有挑战的问题.基于边缘先验模型和小波分析提出了一种运动模糊退化图像的复原算法.在去模糊之前,对图像进行预处理,将噪声去除,用冲击滤波器增强边缘,并采用canny边缘检测获取清晰边缘作为先验模型,以此估计模糊核;然后在紧小波框架系统下,将清晰图像的稀疏性最大化,采用改进的分裂Bregman方法求解最优化问题,最终得到清晰的图像.实验结果表明,相对于传统的盲复原算法,提出的方法可以有效地去除运动模糊.     

基于稀疏表示的医学图像融合

针对传统基于K阶奇异值分解(KSVD)的字典学习算法时间复杂度高,学习字典对源图像的表达能力不理想,应用于医学图像融合效果差的问题,提出了一种新的字典学习方法:在字典学习之前对医学图像的特征信息进行筛选,选取能量和细节信息丰富的图像块作为训练集学习字典;根据学习得到的字典建立源图像的稀疏表示模型,运用正交匹配追踪算法(OMP)求解每个图像块的稀疏系数,采用"绝对值最大"策略构造融合图像的稀疏表示系数,最终得到融合图像.实验结果表明:针对不同的医学图像,提出的方法有效.     

基于视觉传达的多帧图像高分辨率重建仿真

针对传统的高分辨图像重建方法,重建之后的图像细节不够丰富清晰,边缘模糊的问题,提出了 一种基于视觉传达的多帧图像高分辨率重建方法.采用深度学习方法提取高分辨率图像的深层次特征,在稀疏字典超分辨率框架下联合训练特征字典,将提取出来的特征视为ScSR模型中的特征样本,代入PCANet的特征字典中,以此为基础,基于稀疏正则模型对高分辨率图像进行重建,在反向投影全局优化模型基础上引入非局部近似性先验约束对重建图像进行优化,完成多帧图像高分辨率重建优化.实验结果表明,所提方法与其它传统方法相比,图像重建效果更好,图像边缘更加清晰.     

基于变分贝叶斯推断的字典学习算法

传统的字典学习算法在对训练图像进行学习时收敛速率慢,当图像受到噪声干扰时学习效果变差.对此,提出一种基于变分推断的字典学习算法.首先设定模型中各参数的共轭稀疏先验分布;然后基于贝叶斯网络求出所有参数的联合概率密度函数;最后利用变分贝叶斯推断原理计算出各参数的最优边缘分布,训练出自适应学习字典.利用该字典进行图像去噪实验以及压缩感知重构实验,仿真结果表明,所提出的算法可显著提高字典学习效率,对测试图像的去噪效果和重构精度有很大改善.     

基于自然图像块相似性和稀疏先验性的图像复原

针对物体成像过程受光学系统散焦、运动、大气扰动及光电噪声等因素影响,导致光学系统获取的图像存在噪声、模糊、畸变等降质问题,对基于自然图像块相似性和自然图像稀疏先验信息的图像复原方法进行研究,提出一种泛化的基于图像块相似性和自然图像稀疏先验的图像复原框架。首先,在研究自然图像稀疏先验模型的基础上比较了几种图像块的相似性模型,比较结果表明在图像复原中利用图像块的高相似性先验条件模型能够提升图像复原的性能;接着,构建和优化了基于图像块的期望log相似性模型,减少了运行时间,简化了学习过程;最后,通过构建一种近似的最大后验估计（MAP）算法,最终实现了基于优化的期望块log相似性和混合高斯模型（GMM）的图像复原。仿真实验结果表明,所提方法能够很好地复原包含有各种模糊和加性噪声的退化图像,所得图像的峰值信噪比（PSNR）和结构相似度（SSIM）都优于当前技术条件下的其他稀疏先验复原方法,并具有更好的视觉效果。     

基于L-R非线性迭代的降质图像复原算法

为克服图像传输和获取过程中受模糊、失真等因素影响所造成的图像降质,提出一种基于L-R非线性迭代的降质图像复原算法。建立图像退化和恢复模型,并给出复原图像的评价测度。仿真实验结果表明,与传统的维纳滤波相比,该算法在存在多种随机噪声的情况下,能达到较好的图像复原效果。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.