紧耦合多传感器混合跟踪算法

在增强现实应用中实现对运动目标的准确跟踪是一个具有挑战性的任务。基于混合跟踪通过对多传感器信息的融合通常比单一传感器跟踪算法更为优越的特性,提出了一种新的紧耦合混合跟踪算法实现视觉与惯性传感器信息的实时融合。该算法基于多频率的测量数据同步,通过强跟踪滤波器引入时变衰减因子自适应调整滤波预测误差协方差,实现对运动目标位置数据的准确估计。通过标示物被遮挡状态下的跟踪实验结果表明,该方法能有效改善基于扩展卡尔曼滤波器的混合跟踪算法对运动目标位置信息预测估计的准确性,提高跟踪快速移动目标的稳定性,适用于大范围移动条件下的增强现实系统。     

融合目标形状信息及图割窄带优化的目标跟踪算法

提出基于图割窄带优化算法及融合目标形状信息的目标跟踪方法,首先采用卡尔曼滤波方法对目标新的位置进行预测,进而基于目标当前位置及分割结果估计目标的形状的信息,然后在目标预测位置采用窄带的图割优化算法并集成目标的形状先验信息对目标的进行分割,从而确定目标新的位置并得到目标新的轮廓结果,完成目标的精确跟踪。实验结果表明提出的方法具有良好的性能,能够精确有效的跟踪复杂背景中的运动目标。由于采用窄带图割分割优化,使得算法也具有良好的实时性,能够在实际中得到应用。     

WSN中利用改进FOA-GRNN和迭代Cubature卡尔曼滤波的实时目标跟踪方法

针对传统无线传感器网络(Wireless Sensor Network,WSN)对运动目标的定位和跟踪容易产生明显误差的问题,提出利用改进FOA-GRNN和迭代Cubature卡尔曼滤波的实时目标跟踪方法.基于改进FOA-GRNN法,利用从锚点接收到的运动目标的模拟(RSSI)值和相应的实际目标二维位置对GRNN进行训练,从而获得单个目标在二维运动时的准确初始位置;利用迭代Cubature卡尔曼滤波法对实时目标进行精准定位和测距,获得实时目标的准确定位和跟踪信息;将改进的FOA-GRNN法和迭代Cubature卡尔曼滤波法相结合用于WSN中实时目标跟踪和定位,在提高初始位置精度的同时,还提高了实时目标定位和跟踪信息的准确度.实验结果表明,相比其他几种较新的方法,该方法改善了WSN中实时目标的跟踪性能,降低了误差,提高了跟踪精度.     

基于模糊熵高斯聚类的弱点状动目标跟踪技术

研究了一种基于最大模糊熵高斯聚类的实时图像目标跟踪算法:在目标初始信息(位置、速度)已知的情况下,应用最大模糊熵高斯聚类的方法进行跟踪窗内测量点融合,将融合后的点输入到Kalman滤波器中进行预测目标点下一个状态的位置,在预测位置继续开一个跟踪窗进行检测、融合,直至所有图像都被跟踪完为止。理论及实验结果表明,在序列图像情况下该算法能够在保持跟踪实时性的同时,提供较高的跟踪精度。     

基于深度相机的移动机器人视觉跟踪控制研究

基于视觉利用移动机器人进行运动目标跟踪,该文提出一种基于二自由度云台和RGB-D相机的运动目标视觉跟踪及移动机器人路径实时规划、跟踪方法。该方法利用核相关滤波算法在图像中实时追踪目标,控制二自由度云台使深度相机实时对准目标,并根据深度相机得到目标的深度信息,利用坐标转换得到目标相对于机器人的位置信息;其后移动机器人根据目标的位置信息,基于五次多项式进行路径规划;最后采用李雅普诺夫控制律对移动机器人进行轨迹跟踪控制,使得机器人能够平稳地跟踪目标运动。该算法在阿克曼移动机器人上进行了实验,实验结果验证了算法的有效性和实时性。     

交互式多模型算法的MT-R机器人视觉跟踪

针对机器人的视觉跟踪问题,提出了一种基于交互式多模型算法的视觉跟踪方法。该方法采用HSV颜色模型,通过交互式多模型算法进行滤波估计,获得目标的运动属性。利用交互式多模型算法对目标的位置进行一步或者N步预测,在获得下一帧的观测值后,在预测位置的区域进行目标搜索,可减少搜索区域,节省搜索时间,增加了跟踪的实时性。使用该方法对机器人足球比赛中的红色球进行搜索跟踪。实验结果表明,应用该方法可获得目标的运动属性,能快速搜索到运动目标,并能进行准确跟踪。     

基于灰色预测的无人水下航行器目标跟踪

针对无人水下航行器目标跟踪控制问题,基于无人水下航行器传感器信息进行目标运动预测来实现跟踪控制。从目标预测理论出发,将灰色动态预测模型的建模原理引用到目标预测中,在对传感器进行数据滤波、小样本灰色建模与灰色动态预测的基础上,实现对目标运动的预测,文章详细阐述了基于灰色动态预测的传感器故障诊断的具体实现方法和步骤,对目标进行匀速运动、匀加速运动、变加速运动三种典型运动进行仿真研究,通过预测值与实际值之间的比较显示灰色预测方法能快速、准确的预测出目标的位置信息。     

一种基于无人机云台的视觉目标跟踪方法

鉴于无人机视觉目标跟踪时会遇到目标遮挡、目标尺度变化等问题,同时目标跟踪方法复杂度受到云台芯片算力的严格限制,提出了一种基于无人机云台的视觉目标跟踪方法。基于多个特征相关滤波器的自适应权重融合来提升目标位置预测的精度。引入长宽相互独立变化的尺度变化池策略,解决无人机目标跟踪过程中目标尺度估计问题。通过设置模板检测和轨迹预测模块来有效地对目标跟踪过程中的遮挡状态进行检测和处理。该方法可在无人机云台芯片中实现实时跟踪,且在公开无人机目标跟踪数据集和自采集数据集中取得了很好的跟踪效果,与基线方法相比,成功率提升了10.7个百分点,准确率提升了3个百分点。     

深度学习的目标跟踪算法综述

目标跟踪是利用一个视频或图像序列的上下文信息,对目标的外观和运动信息进行建模,从而对目标运动状态进行预测并标定目标位置的一种技术,是计算机视觉的一个重要基础问题,具有重要的理论研究意义和应用价值,在智能视频监控系统、智能人机交互、智能交通和视觉导航系统等方面具有广泛应用。大数据时代的到来及深度学习方法的出现,为目标跟踪的研究提供了新的契机。本文首先阐述了目标跟踪的基本研究框架,从观测模型的角度对现有目标跟踪的历史进行回顾,指出深度学习为获得更为鲁棒的观测模型提供了可能;进而从深度判别模型、深度生成式模型等方面介绍了适用于目标跟踪的深度学习方法;从网络结构、功能划分和网络训练等几个角度对目前的深度目标跟踪方法进行分类并深入地阐述和分析了当前的深度目标跟踪方法;然后,补充介绍了其他一些深度目标跟踪方法,包括基于分类与回归融合的深度目标跟踪方法、基于强化学习的深度目标跟踪方法、基于集成学习的深度目标跟踪方法和基于元学习的深度目标跟踪方法等;之后,介绍了目前主要的适用于深度目标跟踪的数据库及其评测方法;接下来从移动端跟踪系统,基于检测与跟踪的系统等方面深入分析与总结了目标跟踪中的最新具体应用情况,最后对深度学习方法在目标跟踪中存在的训练数据不足、实时跟踪和长程跟踪等问题进行分析,并对未来的发展方向进行了展望。     

基于信道状态信息的被动式目标轨迹跟踪方法

针对目前的被动式目标人员轨迹跟踪方法计算开销大,算法复杂度高等问题,提出了一种基于信道状态信息CSI(Channel State Information)的被动式目标人员跟踪方法。该方法在离线阶段采集细粒度的CSI数据,建立离线指纹数据库;在线阶段,将实时数据与离线数据库中的数据利用融合了卡尔曼滤波的KNN位置指纹算法进行匹配,实现目标人员轨迹跟踪。实验结果表明该方法可以更精确的跟踪目标人员的轨迹,跟踪可靠性更高。     

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。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。