一种自适应的双门限场面运动目标检测方法

为了有效解决在复杂环境下机场场面运动目标的精确检测问题,提出了一种自适应的双门限场面运动目标检测方法.首先采用混合高斯背景模型的方法来提取背景图像,然后使用两个门限值对差分图像进行前景目标分割,低门限阈值用于粗分割以检测出较明显的运动目标,在粗分割的基础上再用高门限阈值进行细分割以去除噪声目标和伪目标,最终得到场面运动目标的准确检测和分割结果.在复杂条件下的场景进行的实验,验证了该方法具有良好的噪声抑制能力和对慢目标良好的鲁棒性,同时能有效地分割出前景目标.     

视频序列中自适应背景的运动目标提取

在视频序列的运动目标实时检测中常用的方法是背景差分法,但因背景图像未随监视场景光照变化及时更新而限制了本方法的适应性.对此,本文首先提出了一种自适应背景更新方法,得到差分二值图像;然后引入散布函数准则计算出差分图像的最佳分割阈值,实现运动目标的自适应阈值分割.实验结果表明:本文提出的背景更新方法可随着光照条件的变化实时、准确地更新背景图像,在此基础上提出的基于散布函数准则的自适应阈值分割方法可以实现运动目标的完整分割,这为运动目标的后续识别与理解奠定了基础.     

海天背景下港口船舶检测算法研究

针对海面视频图像中目标船舶总是出现在海天线附近且海面经常出现间断性不连续杂波和孤立噪声点的问题,采用边缘检测、阈值分割与霍夫线检测结合的方法检测出海天线.去除海天线及以上背景,准确定位目标船舶.采用局部自适应阈值分割去除海面由于漩涡产生的间断性杂波,分割出真实目标船舶.通过形态学处理来填补目标船舶中间出现的空洞,连通域面积检测去除静止点来消除对目标点的影响.实验结果表明:该方法能有效地去除海面杂波和噪声点等对目标的干扰,有效检测出海面背景下的目标船舶.     

一种快速的视频序列运动分割方法

提出一种视频序列运动分割的实时方法,该方法通过两次背景更新提取运动前景,其中长程背景更新检测噪声运动区域,并将长时间停留在场景中的物体纳入背景范围,短程背景更新利用单高斯分布模型实现对光线缓慢变化的适应。采用基于颜色空间的方法实现对阴影的消除,通过投影分割提取出不同的运动目标。试验证明该方法能够快速、精确地实现视频序列中多个运动目标的分割,消除背景噪声运动、目标阴影以及场景变化的影响。     

分块帧差和背景差相融合的运动目标检测

提出了一种分块帧差和背景差相融合的运动目标检测方法。该方法利用图像分块建立初始背景模型,将视频图像划分为多个子块,对帧间差分图像的各子块进行自适应阈值检测,完成运动目标的粗分割,采用双阈值背景差分和邻域背景差分法对粗分割出来的运动区域进行细分割。背景采用自适应更新方法,能够克服光照变化和背景干扰。实验结果表明,该方法运算速度快、鲁棒性好,能够准确检测出运动目标。     

基于概率统计自适应背景模型的运动目标检测方法

为了更好地进行运动目标检测,提出了一种基于概率统计的自适应背景模型的运动目标检测方法。该方法能够自适应选择背景和前景阈值,且不需要进行训练,而且在不同的场景下能够自适应进行选择。在此基础上,针对盲目更新和选择更新不足,还采用了像素聚类统计和概率相结合的背景更新模型,因为采用基于像素统计的更新机制能够适应场景中背景的局部改变(移入/移出物体),而采用概率更新则能够降低前景污染背景的程度。实验证明,该方法能够得到可靠的背景,改善了运动检测效果。     

改进视觉背景提取模型的运动目标检测算法

针对视觉背景提取模型对动态场景适应性不强、运动目标检测精度低等问题,提出一种改进的视觉背景模型算法.在模型建立与初始化阶段,采用按序抽取的方法将像素点本身信息加入到背景模型中,形成邻域背景模型,降低复杂场景对模型的影响;在前景检测阶段,结合像素点的空间邻域信息自适应地获取分割阈值,减少各类复杂场景对检测结果的干扰,提高运动目标检测的精度;在背景更新阶段,根据场景复杂度动态地调整模型的更新周期与更新方式,使得模型能够有效地消除虚影与背景噪声的影响,增强模型对复杂场景的适应性与鲁棒性.与典型算法进行对比的实验结果表明,该算法具备较高的检测精度,适用于动态场景中的运动目标检测.     

改进的基于区域的运动目标分割方法

针对视频监控系统，提出了一种改进的基于区域的运动目标分割方法。与传统方法相比，在运动检测阶段，结合时域差分和背景差分进行运动检测。并通过自适应方法进行背景更新；在差分图像二值化时，采用自适应阈值方法来代替传统的手工确定阈值法；对于区域分割，使用基于加权平方欧式距离的均值聚类算法代特传统的均值聚类算法。实验结果表明该改进方法比传统方法具有更好的实时性、鲁棒性和有效性。     

基于改进背景减法的视频图像运动目标检测

为解决传统背景减法在动态背景下受噪声干扰和运动目标检测准确性不高的问题,提出一种基于改进背景减法的视频图像运动目标检测方法。在背景建模阶段,为易于计算和提高检测精度,采用基于GMM的图像块均值方法重构背景模型;在目标检测阶段,采用数学形态学和小波半软阈值函数相结合的方法对检测到的运动目标进行去噪处理;在背景更新阶段,采用自适应背景更新方法进行背景更新。实验结果表明,所提方法提高了运动目标检测的准确性,验证了其有效性。     

一种图像序列自动分割新方法

该文提出了一种固定场景下的图像序列自动分割的新方法。该方法分为两个阶段。在第一个阶段中,巧妙地采用形态学处理方法获得当前帧的运动区域,然后用当前帧对背景进行更新,经过数十帧的迭代,自动提取出初始背景;第二阶段对每帧作如下操作:首根据当前帧与背景的差分图像的直方图提取出噪声参数,并利用该参数求出对差分图像分割的双阈值,从而实现运动目标分割,最后再利用分割结果对背景进行自动更新。试验结果表明,用该方法进行分割不但效果好,而且速度快。     

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.