Multiple collaborative kernel tracking

Those motion parameters that cannot be recovered from image measurements are unobservable in the visual dynamic system. This paper studies this important issue of singularity in the context of kernel-based tracking and presents a novel approach that is based on a motion field representation which employs redundant but sparsely correlated local motion parameters instead of compact but uncorrelated global ones. This approach makes it easy to design fully observable kernel-based motion estimators. This paper shows that these high-dimensional motion fields can be estimated efficiently by the collaboration among a set of simpler local kernel-based motion estimators, which makes the new approach very practical.     

多线索融合的无视野重叠跨摄像机行人跟踪算法

针对单个摄像机视野有限而无法满足日益扩大的监控范围的现象,此文对无视野重叠的跨摄像机行人跟踪算法进行了研究,并提出了一种融合时空线索和外观线索的无视野重叠跨摄像机行人跟踪算法。文章在对已有摄像机网络拓扑结构估计算法分析的基础上提出了一种基于加权时间窗口的无视野重叠摄像机网络拓扑结构估计算法。然后利用朴素贝叶斯完成两种线索融合,实现不同摄像机间行人匹配和跟踪信息的传递,最终实现无视野重叠区域的跨摄像机行人跟踪。该算法在公开的MCT数据集上进行对比实验并取得了优于其它算法的结果。     

基于场景模型的多摄像机目标跟踪算法

在多个相机组成的视频监视系统中,当目标物移出某一相机的视野而进入下一个时,如何实现相机的交接,实现目标物的继续跟踪是监视系统中要解决的关键问题。针对该问题,提出了一种基于位置比较的多摄像机运动目标跟踪方法。为获得目标物的位置,建立多个相机与目标物世界坐标之间映射关系的场景模型,并根据目标物出现在不同相机之间的视野边界线上的瞬间时刻的位置来给出重叠视野的边界线。由此可对任意角度摆放的多个具有重叠视野的相机之间运行的目标物进行接力跟踪。该方法可以适应多个目标物同时进入场景的情况,实验结果表明,该方法具有较高的鲁棒性,能够满足视频跟踪的实时性要求。     

基于GIS的分布式实时协同制图系统的研究

由于Internet网络带宽限制等诸多方面的影响,基于GIS的分布式实时协同制图系统是较难实现的。采用复制式模型构造了一个基于GIS的分布式实时协同制图系统,并且采用动态数据格式作为各站点的交换数据,极大限度地战少了网络数据传输量,提高了系统的响应速度和稳定性,满足了协同制图系统对实时性的要求。     

Multiple Mice based collaborative one-to-one learning

Exchange is a collaborative learning application, originally developed for wirelessly interconnected Pocket PCs, that provides support for students and a teacher performing a face-to-face computer supported collaborative learning (CSCL) activity in a Single Input/Single Display (SISD) mode. We extend the application to support a single display groupware (SDG) mode. In this new version, named Exchange-MM, three users each with their own mouse (Multiple Mice) interact on a single display with mediation by a technological network. The original collaborative interaction is maintained. We describe a collaborative learning activity and the software architecture that supports both interaction modes, and also present a usability analysis of the activity conducted with second-grade schoolchildren. The results show that as in SISD mode, in SDG with Multiple Mice (MM) the technological network improves communication, negotiation, interactivity, coordination and appropriability between members of collaborative learning groups.     

基于工作流的分布式协同计划控制架构研究

从协同的角度研究了制造业在分布式协同制造企业环境下所面临的相关技术问题,提出了基于工作流的分布式协同计划控制架构。该架构分为两层,在企业层对所有协同机构的生产任务进行动态的协同优化调度;在车间层对有限资源在需求约束下进行优化调度。应用扩展的工作流概念和功能去正确地管理活动序列,建立了资源管理、活动调度以及任务协同调度的优化模型。最后,提出了基于规则的更新处理组件用于提高系统自动化程度。     

基于面向对象Petri网的无人机协同追踪系统建模*

从离散事件系统角度出发,基于动态角色配置的思想,提出了协同追踪过程中无人机在搜索、协助者、领导者和空闲四个角色之间切换,动态构建团队追踪地面移动目标的协同追踪策略,采用面向对象Petri网对无人机、移动目标以及协同追踪策略组成的协同追踪系统进行建模研究。利用改进的人工势场法作为无人机的追踪算法,设计了一种协同追踪的情景对协同追踪系统进行了仿真,仿真结果表明了系统建模的可行性。     

基于Hadoop分布式改进聚类协同过滤推荐算法研究

为了改善协同过滤推荐算法在大数据下的稀疏性和可扩展性问题,提出一种基于Hadoop平台的分布式改进聚类协同过滤推荐算法。在分布式平台下,离线对高维稀疏数据采用矩阵分解算法预处理,改善数据稀疏性后通过改进项目聚类算法构建聚类模型,根据聚类模型和相似性计算形成推荐候选空间,在线完成推荐。实验验证该算法能够有效改善推荐系统的推荐质量并大大提高推荐效率,同时在云环境中具有良好可扩展性。     

Personnel tracking on construction sites using video cameras

This paper discusses the possibility of- and need for-tracking workforce on construction jobsites using video cameras. An evaluation of algorithms and their associated results is presented. The principal objective of this paper is to test and demonstrate the feasibility of tracking workers from statically placed and dynamically moving cameras. This paper also reviews existing techniques to monitor workforce and describes areas where this work might be useful in engineering applications. The main difficulties associated with tracking on a construction site is the significant amount of visual clutter, the changing photometric visual content throughout the course of a day, and the presence of occluding and moving obstacles. The tracking of workers within the field of view of the camera will involve four tracking techniques, density mean-shift, Bayesian segmentation, active contours, and graph-cuts. Typical construction site video will be processed using the proposed algorithms and analyzed to determine the most appropriate tracking method for the video presented.     

Multiple human tracking in high-density crowds

In this paper, we introduce a fully automatic algorithm to detect and track multiple humans in high-density crowds in the presence of extreme occlusion. Typical approaches such as background modeling and body part-based pedestrian detection fail when most of the scene is in motion and most body parts of most of the pedestrians are occluded. To overcome this problem, we integrate human detection and tracking into a single framework and introduce a confirmation-by-classification method for tracking that associates detections with tracks, tracks humans through occlusions, and eliminates false positive tracks. We use a Viola and Jones AdaBoost detection cascade, a particle filter for tracking, and color histograms for appearance modeling. To further reduce false detections due to dense features and shadows, we introduce a method for estimation and utilization of a 3D head plane that reduces false positives while preserving high detection rates. The algorithm learns the head plane from observations of human heads incrementally, without any a priori extrinsic camera calibration information, and only begins to utilize the head plane once confidence in the parameter estimates is sufficiently high. In an experimental evaluation, we show that confirmation-by-classification and head plane estimation together enable the construction of an excellent pedestrian tracker for dense crowds.     

Multiple human tracking in drone image

Multimedia Tools and Applications - Object tracking, especially human tracking is one of the challenging research problems in computer vision. Although the performance has gained some positive...     

Multiple person tracking based on slow feature analysis

Multimedia Tools and Applications - Object tracking is one of the most important components in numerous applications of computer vision. However, it still has many challenges to be solved, such as...     

Multiple target tracking based on symmetric measurement equations

An approach to track maintenance in multiple target tracking is presented in terms of measurements which are symmetric functions of target positions. In this approach, the data association problem is embedded in the process of target state estimation so that there is no need to consider possible target/measurement associations. For N targets moving in three-dimensional space, the first-order version of the target state estimator is an extended Kalman filter of dimension 6N. Attention is focused on the case of constant-velocity targets with the number of measurements (of a given coordinate) assumed to be equal to the number of targets     

基于二阶非线性投票的多目标跟踪算法*

提出了基于二阶非线性投票的多目标跟踪算法。该算法通过目标匹配得到同一目标在不同帧中的位置,同时利用特征监测来处理目标的遮挡、分裂问题,并实现目标特征的实时更新。在目标匹配过程中,通过对目标前一帧与当前帧的特征相似性进行投票,得到匹配目标。利用视频图像进行实验,结果表明,该方法对噪声、阴影、遮挡、分裂等具有良好的鲁棒性,较好地实现了多目标的跟踪。     

基于分布式及协同式网络入侵检测技术综述

在当今信息化社会,网络入侵检测技术是信息安全保障领域的重点技术之一。随着大数据时代的到来,网络入侵检测技术正在向着多结构、多方法、多应用领域的方向发展。针对这个发展趋势,综述了网络入侵检测技术的最新研究情况,包括基本概念、系统模型、检测方法、应用领域等,其中重点分析了系统模型和检测算法的研究现状以及存在的问题,并提出发展趋势。同时,也介绍了大数据背景下网络入侵检测技术的新型应用领域。     

Multi-agent negotiation based on price schedules algorithm for distributed collaborative design

Collaborative design is a common practice in modern product development. Companies specializing in different disciplines, which are often geographically separated, work together to develop solutions for the benefit of overall design. In such inter-organizational collaboration, participants hiding individual skills and design rationales is highly desirable. To fulfill this requirement, this study proposes a negotiation mechanism based on a price schedules decomposition algorithm originally developed in economics. The mechanism searches for globally optimal designs, where no participant is necessary to own full knowledge of the entire design space. This paper also applies multi-agent system technologies to realize a secure environment for automating distributed collaborative design. A test scenario of distributed tolerance allocation in assembly design validates the proposed mechanism.     

基于分布式计算框架的风暴三维追踪方法

气象数据的增长规模已达到每小时TB级,这使得传统基于关系型数据库和文件存储系统在海量数据存储与管理方面捉襟见肘,进而使得基于大规模异构气象数据的应用无法规模化,同时,也无法满足科研人员对海量气象数据高效探索的需要。为解决这一系列问题,研究者分别基于MapReduce、HBase等分布式框架下的分布式计算和存储技术,尝试为海量气象数据的探索提供有效技术手段,然而,综合性的研究据了解还未开展。因此,利用近年来积累的海量多普勒天气雷达数据,开展了基于MapReduce和HBase相结合的风暴三维追踪方法的研究,并基于传统Rest标准化接口实现了雷达资料的点、线、面、体的多种分布式服务接口,与传统的Rest标准化单机数据存储和访问接口的性能相比,所实现方法在性能方面有100%的效率提升。最后,以2007年至2009年珠江三角洲地区三年雷达数据的风暴追踪回算为例,进一步验证了所提方法在计算和存储管理方面的性能优势。     

基于分布式数据融合的无线移动传感器网络目标跟踪算法

针对无线移动传感器网络(WMSN)自身具有移动性和分布式的特点,在现有分布式粒子滤波DPF的基础上,提出了一种实现分布式数据融合的分布式目标跟踪算法WDOT。该算法使用高斯混合模型和平均一致性滤波器实现了节点的分布式数据融合,提高了算法的稳定性,降低了通信开销。仿真实验通过与已有目标跟踪算法在通信开销、估计均方根误差等方面的对比,验证了WDOT算法的目标跟踪性能。     

基于Mean Shift的多模板目标跟踪算法

目标跟踪是计算机视觉研究领域的热点之一,并得到广泛应用。其中基于Mean Shift的运动目标跟踪算法因其计算量小,实时性好,简单易行等特点而受到广泛关注,但该算法在目标突变或严重帧丢失以及目标严重遮挡的情况跟踪效果不佳,留下了改进空间。在传统基于Mean Shift运动目标跟踪方法基础上,通过创建并维护多样性模板库为跟踪过程提供更丰富的目标描述信息,提高算法运动目标跟踪效果。实验结果表明,新算法较好地解决了在目标突变和严重帧丢失情况下不能准确跟踪目标的问题,并且对目标的完全遮挡也具有很好的鲁棒性。