一种基于多特征的视频人物聚类方法

检索一段视频中出现的人物并进行人物归类具有重要的研究意义和实用价值.本文提出一种基于多特征的视频人物检索聚类算法:先用一种结合人脸检测和物体跟踪的算法检测镜头人物,并提取人物衣服区域颜色以及声音作为人物特征,再用一种无监督模糊聚类方法对人物进行聚类,最后利用声音特征对聚类结果进行修正.该方法适用于人物数未知的条件下进行无监督的人物聚类.不同类型视频的试验证明该方法有效而实用.     

视频取证中加权聚类人脸识别方法

提出了一种基于特征加权聚类的视频人脸图像识别方法。该方法指定样本人脸图像特征点,通过增加特征点多方向窗口加权计算,使得中心特征点四周各点具有相异权重,利用加权聚类人脸识别方法检测限制搜索区域,最后根据每一个侯选区域的几何信息及人脸特征验证是否为指定人脸。实验结果表明,提出的算法实现简单、误检率低、检测速度快,适合实时视频监控取证系统应用。     

结合对齐度准则的视频人脸快速配准算法

在视频人脸替换过程中,针对人脸检测和特征点定位不考虑前后帧的时域联系,导致处理后的视频人脸出现抖动、错位现象的问题,提出结合对齐度准则的视频序列人脸配准方法。通过人脸特征点定位确定待匹配人脸的候选区域和参考人脸五官图像,并根据梯度信息得到参考人脸搜索子图像。构造图像尺度金字塔,在尺度金字塔中快速搜索对齐度极值,极值坐标对应搜索子图像相似度最高的配准点,构造匹配点对。采用Procrustes analysis算法计算对应匹配点的变换关系矩阵,完成待配准图像的坐标变换。根据实验数据,提出的算法提高了优化搜索的速度,处理后的视频与其他算法相比,前后帧对齐的人脸位置和姿态稳定,经处理的视频播放过程中人脸位置自然流畅。算法消除了肤色区域的影响,采用前后帧人脸的有效信息,保持了灰度变化大的人脸区域的位置和姿态,实现视频人脸的精确配准。     

基于粒子群优化的高斯核函数聚类算法

针对视频帧数据在时间轴上的高斯分布特征,提出基于样本和高斯核相似性度量的聚类算法,采用度量方法考虑概率分布密度因素,同时利用改进的粒子群优化算法加速聚类过程。实验结果表明,与基于C均值聚类算法相比,该算法具有较强的全局搜索能力和聚类精度,在视频数据聚类分析中具有更高的效率和更佳的聚类效果。     

自适应的新闻视频播音员镜头探测方法

提出一种基于聚类算法的新闻视频播音员镜头探测方法。该方法利用人脸探测得到的人脸属性进行聚类,在此基础上利用人物及人物边缘背景区域的颜色特征在聚类的结果中进行聚类分析,确定播音员镜头候选类型。通过背景边缘的颜色相似度分析对播音员镜头候选类型进行完善得到最终的播音员镜头类型。实验证明该方法通用性和效率都比较好。     

基于附加间隔Softmax特征的人脸聚类算法

针对数据量巨大、类别多、真实类别数未知、样本数量不均衡、类内变化多的无标签人脸图像分类问题,提出基于附加间隔Softmax特征的近似等级排序人脸聚类算法。使用附加间隔Softmax损失结合Inception-ResNet-V1网络训练人脸识别模型来提取深度人脸特征,并应用于近似等级排序聚类。在LFW人脸数据集、LFW与视频模糊人脸的混合数据集上进行实验,结果表明该模型在人脸识别准确率、误识率为0.1%时的验证率均优于其他模型,近似等级排序聚类在F1度量得分优于其他聚类算法,具有更强的鲁棒性和应用价值。     

一种基于MTCNN和MobileFaceNet人脸检测及识别方法

随着智能设备的飞速发展,人脸检测技术在安保方面、金融方面等得到了广泛的应用。该文设计一种基于MTCNN和MobileFaceNet算法的人脸检测及识别系统。通过MTCNN算法输出人脸候选框及面部特征关键点坐标,MobileFaceNet算法根据MTCNN输出的人脸面部特征点进行识别判断,最后基于小视科技的静默活体检测算法,对移动人脸进行检测,最终实现活体检测。实验中人脸识别分数阈值设置为0.4,活体检测置信度设置为0.89,误检率较低,满足设计需求。     

引入多尺度特征图融合的人脸关键点检测网络

人脸关键点的精确检测对于人脸姿态矫正、表情识别、疲劳监测等任务具有重要意义。针对当前人脸关键点检测算法对于网络的设计越来越复杂、对计算资源的需求越来越大,网络整体速度变慢,不利于移动端部署的问题,提出了一种基于多尺度关键点热度图融合的人脸关键点检测网络。通过特征图与关键点热度图的融合使网络更多地关注关键点及其周边像素的信息,同时引入了多尺度的关键点热度图融合不断加强网络对于关键点相关信息的学习能力,使用较浅的网络结构就可实现好的检测效果。实验表明该网络在WFLW数据集上取得的检测精度和速度均达到较好的效果。     

基于近邻关系聚合的人脸聚类方法

人脸聚类是人脸标注、人脸识别等工作的预处理过程。其主要对人脸图像进行分组,用来为人脸识别模型提供高质量的标注信息,从而有效降低人工标注的成本。人脸聚类的关键在于如何学习大规模人脸数据中整体及局部的结构关系,并把其迁移至待标注数据集。针对这一问题,本文提出一种基于近邻关系聚合的人脸聚类方法(Nearest Neighborhood Aggregation Clustering, NNAC)。该方法把局部结构的学习建模为一个近邻关系预测问题,通过堆叠多个改进的基于残差-全连接模块(Residual Fully-Connected Block, ResFCB)以提取多尺度的邻接关系特征。实验结果表明,相比主流人脸聚类方法,该方法在基准数据集上能够有效提升聚类精度。     

基于语义人脸的视频新闻标注

视频和图像中的人脸蕴涵了丰富的语义信息，可以使用人脸对视频内容进行分析与标注，尤其是视频新闻节日。而要达到这样的目的，就必须先将对视频新闻具有语义价值的人脸从视频流中检测出来。本文提出基于语义人脸捡测的视频新闻语义聚类与标注算法：在这个算法中，首先使用肤色模型检测人脸可能出现区域，然后提取人脸可能区域的独立成分特征，用训练好的支持向量机检测出所有人脸，套用语义人脸模板过滤出最终的语义人脸集合，最后通过高斯混合聚类，将视频新闻标注为主持人镜头、访谈类新闻镜头和其他新闻故事镜头三类。实验表明，该算法在视频新闻结构化中可以得到较好的应用。     

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.