融入深度特征的多模板相关滤波跟踪算法

针对现实场景中跟踪算法因背景杂乱、遮挡、尺度变化、目标形变等情况易导致跟踪失败的问题,提出融入深度特征的多模板相关滤波跟踪算法.首先对图像或图像区域分别提取深度特征和Color Name特征,经过核相关滤波器学习得到不同的模板;然后采用核相关滤波跟踪算法获得2个特征下的响应集合,并对所得到的集合进行加权融合得到最终的目标位置;最后使用贝叶斯统计通过最大化后验的方式估计最佳目标尺度,同时更新核相关滤波器参数,以实现自适应尺度的目标跟踪.在OTB2013和OTB2015这2个基准数据库上进行实验,并与当前6种优秀的算法进行比较,结果表明该算法性能最优,在2个数据集上的成功率OP(AUE)较KCF算法分别提升10.7%和12.4%.     

基于特征鉴别性分析的变尺度核相关滤波跟踪算法

针对核相关滤波跟踪算法对场景依赖及无法适应目标尺寸变化问题,提出了一种特征鉴别性选择分析的变尺度核相关滤波跟踪算法。在核相关滤波跟踪框架内,提取目标的颜色、纹理、梯度特征,建立样本集合,以最小均方损失函数设定各特征样本权重,鉴别性地选择出最优和次优的两种特征进行自适应融合。在此基础上,利用高斯金字塔构建一维尺度相关响应滤波器,对目标的尺度变化进行估计;通过主旁瓣均值比对融合后的跟踪结果进行评判,实现模板的差异化更新。理论分析和实验表明:所提算法在遮挡及光照变化场景具有较高的跟踪精度并对目标的尺度变化具有一定的估计能力。     

核相关滤波跟踪算法的尺度自适应改进

针对基于检测的核相关滤波跟踪（CSK）算法难以适应目标尺度变化的问题,提出多尺度核相关滤波分类器以实现尺度自适应目标跟踪。首先,采用多尺度图像构建样本集,训练多尺度核相关滤波分类器,通过分类器对目标的尺度估计实现目标的最佳尺度检测;然后,在最佳尺度下采集样本在线学习更新分类器,实现尺度自适应的目标跟踪。对比实验与分析表明,本文算法在目标跟踪过程中能够正确适应目标的尺度变化,相比CSK算法,偏心距误差减少至其1/5~1/3,能满足复杂场景长时间跟踪的需求。     

一种基于核相关滤波的视觉跟踪算法

视觉跟踪是计算机视觉的一个重要方向,而核相关滤波(KCF)跟踪是视觉跟踪领域中的一种比较新颖的方法,它不同于传统基于目标特征的方法,不仅具有较高的跟踪精度,而且具有较快的跟踪速度,在实际应用中效果显著。但当物体快速运动或存在较大尺度变化等时,该方法无法准确地跟踪目标。文中提出的基于核相关滤波器的改进算法有效地解决了上述问题,其通过随机更新多模板匹配,确定了核相关滤波的学习因子,从而实现了学习因子自适应更新模型。实验结果表明,该算法根据不同的场景能快速地调整学习因子,从而提高跟踪的成功度。通过自适应学习因子和多模板匹配,该算法对部分遮挡、光照和目标尺度变化具有较强的适应性。     

基于低秩投影中稀疏误差矩阵分析的视觉跟踪

单目标跟踪是计算机视觉的重要组成部分,其鲁棒性一直受到目标遮挡、光照变化、目标尺度变化等因素的制约。针对这个问题,提出了基于低秩投影中稀疏误差矩阵分析的视觉跟踪算法。为了克服模板漂移对跟踪的影响,采用目标模板和候选目标的相似性关系动态选择目标模板的更新方式。在粒子滤波的框架下,利用鲁棒主成分分析和低秩投影原理求得候选目标的稀疏误差矩阵,根据稀疏误差矩阵的边缘信息和平滑度信息实现对下一帧目标的观测似然估计。在多个视频序列上的实验表明,算法具有较好的鲁棒性。     

基于自适应分块表观模型的视觉目标跟踪

针对表观发生剧烈变化时的目标跟踪问题, 提出一种新的基于自适应分块表观模型的视觉目标跟踪算法. 将目标表观描述为一组具有内在空间上几何结构关系约束的局部图像块, 在跟踪过程中通过自动添加和删除局部图像块适应目标的表观变化, 同时利用全局颜色属性值确定新的图像块的位置, 克服了传统分块算法不能及时更新表观模型的局限性. 实验结果表明, 所提出算法对表观变化具有较高的自适应性, 在表观发生剧烈变化时可实现准确的目标跟踪.

     

联合判别式核相关滤波视觉跟随算法

目标跟踪算法是计算机视觉领域的热门技术之一,拥有广阔的发展前景。核相关滤波视觉跟踪算法由于循环矩阵构造正负训练样本,避免求逆的大量运算,显著提高计算速度而受到广泛关注。但是,核相关滤波算法存在一定局限性,无法应对现实环境存在的遮挡、目标尺度变化、背景模糊等复杂多变的干扰因素。因此提出一种改进型核相关滤波算法。该算法不仅融合多种颜色特征提高图像处理的准确度,而且通过构建自适应尺度变化策略来应对目标尺度变化的挑战。为了进一步区分目标和背景信息,提出联合判别式背景感知与干扰判别的策略,以充分利用目标上下文信息。相比于传统核相关滤波算法,改进算法的精度更高,鲁棒性更强。通过在视频数据集OTB-50上的实验可得,改进后的核相关滤波算法性能获得较大提升。     

基于循环核矩阵的自适应目标跟踪算法

针对现在存在的基于分类的目标跟踪算法难以实现自适应目标大小变化的问题,提出并实现了基于循环核矩阵的自适应目标跟踪算法。算法首先在包含目标的感兴趣区域内采集所有的训练样本以构成一个循环矩阵结构,再使用高斯核函数构造出循环核矩阵,最后通过基于循环核矩阵的分类器的封闭形式的解进行训练和检测。同时,将比较成熟的循环矩阵理论与傅里叶分析建立连接,从而实现了在快速傅里叶变换下进行快速学习和检测。在此基础上,通过分类器对目标响应度的变化,实现自适应目标大小的变化。与一些经典的和较新的自适应目标跟踪算法进行比较,实验结果表明该算法在一定场景下能够更加准确和有效地表达目标的变化。     

结合背景空间信息的相关滤波目标跟踪算法研究

目标检测跟踪算法在智能监控和人机交互中有着广泛的应用,而复杂场景下的跟踪技术研究在计算机视觉领域中具有重要的理论意义和商业价值。为解决复杂场景(光照变化、尺度变化、遮挡等)中由于主客观因素变化所导致的目标漂移问题,采集目标区域相邻的背景图像块来获得更多的背景特征,并将背景图像块添加到目标函数中来实现对目标图像块的限制。将结合了背景空间信息的方法集成到相关滤波器框架上,在现有公开数据集上进行实验。实验结果表明,在一些复杂场景下的跟踪效果得到了改善和提高,能够在不影响帧率的情况下,有效提高目标跟踪的成功率和准确性,优于其他相关滤波跟踪器。     

核相关滤波与孪生网络相结合的目标跟踪算法

针对核相关滤波目标跟踪算法中对局部上下文区域图像提取的HOG特征图在复杂环境下不能保证目标跟踪的精度问题,提出了一种核相关滤波与孪生网络相结合的目标跟踪算法.首先在首帧输入图像中提取HOG特征图并建立相关滤波器模板,同时提取经过孪生网络的目标区域图像特征图;然后若后续帧输入图像帧数不为5的倍数则提取仿射变换HOG特征图,否则提取经过孪生网络的搜索区域图像特征图;最后根据遮挡处理的结果自适应获取目标位置并更新模型和最终相关滤波器模板.仿真实验结果表明本文算法在保证目标跟踪精度的前提下具有满足实时跟踪要求的跟踪速率.     

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.