一种基于多分类器融合的人体运动行为识别模型

为了提高基于智能设备的人体日常行为识别的准确率,针对不同智能设备内置加速度传感器获取的三轴加速度信息,提出了一种基于多分类器融合的行为识别MCF(Multiple Classifier Fusion)模型。针对5种日常行为(静止、散步、跑步、上楼及下楼),优选出与每种行为相关度高的特征集,用于训练对每种行为识别效果最佳的5个基分类器,并采用一个融合器对5个基分类器的输出进行融合处理,得到最终行为识别结果。该模型对这5种行为的平均识别准确率和可信度分别达到96.84%和97.41%,能有效进行用户行为识别。     

高可信度加权的多分类器融合行为识别模型

为了提高基于智能移动设备的人体日常行为识别准确率,提出一种高可信度加权的多分类器融合行为识别模型（MCFM）。针对不同智能设备内置加速度传感器获取的三轴加速度信息,优选出与人体行为相关度高的特征集作为该模型的输入,将决策树、支持向量机以及反向传播（BP）神经网络三个基分类器通过高可信度加权投票算（HRWV）法训练出一个新的融合分类器。实验结果表明,所提出的分类器融合模型能有效提高行为识别的准确率,对静止、散步、跑步、上楼及下楼五种日常行为的平均识别准确率达到94.88%。     

基于人体关节点多特征融合的暴力行为识别

针对目前视频中暴力行为识别算法识别准确率不高的问题,提出一种基于人体关节点多特征融合的暴力行为识别方法。使用YOLO-Pose算法实现人体检测与姿态估计,获取人体关节点位置信息,基于人体结构提取关节点的距离特征和形状特征,基于运动特性提取关节点的动态特征和姿态特征,将所有特征信息进行融合,构建Bi-LSTM行为识别模型实现暴力行为识别分类,并设计行为识别结果稳定器,解决识别过程中因随机干扰导致的行为误判问题。在公开暴力行为数据集Violent-Flows与自制暴力行为数据集Vio-B上验证提出方法的有效性,实验表明,在Violent-Flows数据集与Vio-B数据集上本方法准确率分别达到97.9%与98.5%,高于现有方法。     

一种位置无关的多模型移动用户行为识别方法*

针对智能手机佩戴位置多样性对移动用户行为识别结果的影响,提出一种位置无关的多模型移动用户行为识别方法。该方法通过计算手机加速度传感器所采集到的行为信号在不同佩戴位置的特征相似度,与预先计算的不同佩戴位置特征相似度进行比较,并采用相似度最大的位置特征作为测试样本,利用极速学习机ELM（Extreme Learning Machine）分类器对移动用户行为进行识别。实验结果证明,相对于不区分佩戴位置的行为识别方法,本方法可将识别准确率提高11%,是一种有效的移动用户行为识别方法。     

基于复合时空特征的人体行为识别方法

为了有效地表征人体行为中的姿势信息和运动信息,提高行为识别算法的准确率,提出一种融合三维方向梯度直方图特征与光流直方图特征的复合时空特征,并利用其进行人体行为识别.首先采用复合时空特征综合描述三维时空局部区域的像素分布和像素变化;然后构建复合时空特征词典,并根据该特征词典完成对人体行为序列特征集合的描述;最后采用主题模型构建人体行为识别算法,对行为序列中提取的复合时空特征进行分类,实现人体行为的识别.实验结果表明:该方法能有效地提高人体行为识别准确率.     

基于FMCW雷达和ResNeSt-GRU的行为识别方法

针对FMCW雷达在行为识别方面的应用,提出一种基于分离注意力残差神经网络（ResNeSt）和门控神经单元（GRU）的人体行为识别系统。使用调频连续波（FMCW）雷达采集人体行为数据,之后采用快速傅里叶变换算法（FFT）提取雷达数据每一帧距离、速度和角度维信息,按照时间维度拼接成距离时间图（RTM）、多普勒时间图（DTM）和角度时间图（ATM）,最后以RTM、DTM和ATM作为输入样本,采用三流ResNeSt-GRU模型对不同人体行为进行识别。实验结果表明,三流ResNeSt-GRU模型对8种行为的平均识别准确率达到了98.92%,均高于传统和融合式深度学习模型。此外,采用该模型比传统特征融合之后采用单流网络的识别准确率提高了2.3%。因而该系统可以有效提高人体行为识别系统的识别准确率,为人体行为识别提供新的技术方法。     

基于移动群智感知的极端驾驶行为感知方法

为提高驾驶安全性，减少交通事故的发生，本文提出一种基于移动群智感知的极端驾驶行为识别方法。对收集到的用户智能手机相关传感器的数据进行预处理，进而利用动态步数检测和随机森林等方法来识别乘客的用户情境信息。针对不同的极端驾驶行为，选取不同位置乘客的智能手机来进行数据的收集，综合考虑乘客的手机放置位置因素所造成的相关影响，实现多特征融合的极端驾驶行为感知。针对不同位置的乘客所感知的结果不一致问题，提出采用贝叶斯投票模型来解决。通过真实数据实验，结果表明本文方法能够有效地识别出司机的极端驾驶行为。     

基于关节空时特征融合的人体行为识别

针对现有人体行为识别技术存在的准确率不高和易受环境干扰等缺点,提出一种基于空时特征融合的人体行为识别方法。通过OpenPose提取人体骨骼关节的位置信息用于构造空时融合特征,该特征综合各类行为的空域和时域信息,使得特征表示更具区分度。利用核化主成分分析算法进行特征维度缩减,利用XGBoost算法进行特征分类,获得识别结果。该方法在Multiview Action 3D数据集上进行测试,得到了94.52%的识别率,较现有的其它许多人体行为识别方法表现更好。     

实时面部捕捉技术在虚拟演播室中的应用研究

针对虚拟演播室应用中常见的人体和人脸捕捉与重建的特征识别数据量大、计算耗时长、识别准确率较低、易于导致跟踪失败等问题,提出了一种基于单摄像头的人脸识别和参数化的方法.方法 基于MTCNN技术获取人脸的轮廓和特征点坐标,然后基于SFM人脸标准模型进行特征拟合,实时计算并得到摄像头画面对应的人脸模型顶点和三角面信息,从而实现数据驱动的虚拟人效果.借助这一算法,开发了虚拟演播室应用中的人体和人脸捕捉与重建原型系统.实验表明,上述算法识别特征数据快、识别准确率高、运行速度快,克服了跟踪失败问题、设备成本低,运行效果平滑稳定,用户反馈良好.     

一种基于自相关函数特征的行为识别方法

为了增强特征敏感度,提高人体日常行为识别准确率,提出一种基于自相关函数的人体行为识别方法。首先对预先采集的人体行为数据进行预处理,然后从时域和频域提取特征后计算得到自相关函数特征,同时采取互相关函数的步进式方法在自相关函数上进行降噪操作。分别使用C4.5决策树、K最邻近(KNN)、支持向量机(SVM)、朴素贝叶斯(Naive Bayesian)四种分类器进行分类。实验结果表明,与选取纯粹的时、频域特征集进行识别分类的模型相比,选用了包含自相关函数特征的特征集构造出来的模型对行为的识别准确率有较大提高。     

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     

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。