基于SIFT特征匹配和动态更新背景模型的运动目标检测算法

运动摄像机情况下的运动目标检测是视频监控中的难点和热点问题。为了能够有效地检测出运动目标,提出了一个基于SIFT（Scale Invariant Feature Transform）特征匹配和动态背景建模的背景差算法。首先利用SIFT算法提取特征点,采用RANSAC（Random Sample Consensus）方法求得仿射变换模型参数并实现图像的全局运动补偿,然后用背景差方法实现运动目标的检测,同时进行阴影和鬼影的去除。SIFT特征点匹配的准确性和RANSAC方法去除异常点的有效性使得仿射变换模型参数计算准确,动态更新背景模型的背景差则完整地检测出了前景目标。与Ninad Thakoor实验结果对比说明：该算法能够准确地检测出运动目标,并且保持了前景目标的完整性。     

非结构化道路中基于均质雾天的摄像机动态标定算法

现有的交通摄像机标定算法大多基于车道线长度、车辆尺寸等先验信息,由于在非结构化道路中往往不存在车道线,使得标定算法具有局限性.为了改进摄像机标定在非结构化道路中的适用性,结合摄像机线性模型与均质雾天,提出一种只包含路面以及运动车辆的摄像机动态标定算法.首先生成并更新背景和场景活动图,提取路面、天空的纹理特征,利用区域搜索算法得到感兴趣区域,并根据感兴趣区域的像素变化规律判断当前天气是否为均质雾天;其次根据暗原色先验原理计算场景透射率,将结果映射到[0,255]作为图像显示;最后结合均质雾天光线传输模型、摄像机线性模型和暗原色先验原理导出标定方程,选取路面上具有特定透射率的8个点生成2个一次方程、1个二次方程和1个三角方程,依次标定摄像机参数,将视频多帧图像标定的参数值平均得到准确值.与角点检测法、摄像机6点标定法以及基于消失点的标定算法进行对比的实验结果表明,该算法是有效的且满足视频的实时性处理要求.     

交通监控场景下的相机标定与车辆速度测量

针对交通监控场景中对车辆速度测量的需求,提出了一种相机标定方法和车辆速度测量方案。首先,通过深度学习YOLO检测算法和光流跟踪算法对图像中的车辆目标进行检测和跟踪,根据获得的轨迹集合使用级联霍夫变换计算出道路方向上的消失点,从而检测出道路上的标志线。之后根据消失点和标志线,使用试探焦距思想完成相机标定任务。最后通过计算多帧之间瞬时速度的平均值来实现车辆速度的测量。通过真实交通监控场景的实验结果表明,这种基于消失点的自动相机标定方法具有较好的稳定性和较高的标定精度,能够满足车辆速度测量和实际工程应用的需求。     

结构化道路的实时动态跟踪算法

设计了一种基于完形的双车道结构模板以及它的模板匹配度函数,并将它用于单摄像机跟踪高速公路的道路标志线.算法在跟踪阶段利用历史检测信息动态生成检测模板,保持标志线的跟踪.实验表明,算法具有较好的鲁棒性,并且计算量小,满足系统的实时性要求.     

基于张量投票的摄像机自标定方法研究

针对传统的基于Kruppa方程摄像机自标定算法的欠鲁棒性,首次提出将鲁棒的张量投票算法用于摄像机自标定方法中。利用基于尺度不变的SIFT算法查找并匹配出每对图像的特征点,其中待匹配图像由摄像机对同一场景从三个不同角度位置拍摄,对图像张量投票后按棒张量特征值降序排序,由此筛选得到具有鲁棒性边缘特征的前八对特征点,利用八点算法求解相应的基础矩阵和极点,根据Kruppa方程和三维重建（SFM）算法求得摄像机参数矩阵。实验结果证明,该方法具有较高标定精度,并通过加入高斯噪声的仿真实验证明该算法是一种鲁棒的摄像机自标定方法。     

基于投影仪和摄像机的结构光视觉标定方法

为实现基于投影仪和摄像机的结构光视觉系统连续扫描,需要计算投影仪投影的任意光平面与摄像机图像平面的空间位置关系,进而需要求取摄像机光心与投影仪光心之间的相对位置关系。求取摄像机的内参数,在标定板上选取四个角点作为特征点并利用摄像机内参数求取该四个特征点的外参数,从而知道四个特征点在摄像机坐标系中的坐标。利用投影仪自身参数求解特征点在投影仪坐标系中的坐标,从而计算出摄像机光心与投影仪光心之间的相对位置关系,实现结构光视觉标定。利用标定后的视觉系统,对标定板上的角点距离进行测量,最大相对误差为0.277%,表明该标定算法可以应用于基于投影仪和摄像机的结构光视觉系统。     

基于马尔算法的高速公路视频监控图像能见度研究

根据高速公路沿线的监控摄像机,对监控视频画面中的图像进行采集,通过对视频图像特征的分析处理,建立图像与真实场景之间的关系,根据图像特征随着真实场景的变化,运用图像处理的方法如：灰度变换、图像分割和特征提取等对图像进行图像处理,提出运用马尔算法,分别提取出目标物与背景,并将其逐一进行背景差计算,能够准确的监控图像中汽车的位置变化,确定目标物的位置,进而判别出能见度的大小。     

摄像机运动情况下的运动对象检测

在监控应用中,由于场景是已知的,因此可以使用背景减去法检测运动对象.当摄像机进行扫描和倾斜运动时,需要使用多个图像帧才能完整地表示监控场景.如何组织和索引这些背景帧属于摄像机跟踪问题.提出一种无需摄像机标定的背景帧索引和访问方法.这一方法需要使用图像配准技术估计图像初始运动参数.提出一种屏蔽外点的图像配准算法,综合利用线性回归和稳健回归快速估计初始运动参数.为了快速计算连续帧之间的运动参数,提出一种基于四参数模型的优化算法.利用非参数背景维护模型抑制虚假运动象素.室内和户外实验结果表明本文方法是有效的.     

基于动态模板的实时道路跟踪*

设计了一种基于双车道的结构模板及其模板匹配度函数,并将它用于单摄像机跟踪高速公路的道路标志线。在模板初始化成功后,算法在跟踪阶段利用历史检测信息动态生成检测模板,在更小的范围内保持标志线的跟踪。算法利用了高速公路车道的整体结构信息进行标志线的检测和跟踪。实验表明,该方法具有较好的鲁棒性,并且计算量小,满足系统的实时性要求。     

基于SIFT特征匹配与K-均值聚类的运动目标检测

运动摄像机情况下的运动目标检测是视频监控中的难点和热点问题。为了能够有效地检测出运动目标,根据视频中背景与运动目标的速度不同这一特点,提出了一个基于尺寸不变特征变换(SIFT)和K-均值聚类的运动目标检测方法。首先提取视频中相邻两帧图像的SIFT特征点并进行匹配,并计算匹配特征点的运动速度,最后将运动目标和背景上的SIFT特征点K-均值聚类分析,在单运动目标、多运动目标和带有摄像头旋转情况下做了实验。实验结果表明,提出的目标检测算法能够在运动背景下较好地检测到目标并保留稳定的目标局部特征,对于摄像机运动、摄像机旋转、亮度变化等影响因素具有较强的适应能力。     

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。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

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.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.