Fast and effective color-based object tracking by boosted color distribution

In this paper, we propose a novel tracking algorithm, boosted color distribution (BCD), for tracking color objects. There exist three contributions in this paper. First, we propose a novel online gentle boost (OGB) algorithm for online learning. The essential idea of OGB is composed of two aspects: online updating candidate weak classifiers, and then choosing and combining them in a boosting way. Second, we design a novel weak classifier, log color feature distribution ratio, which focuses on the difference of color distributions rather than individual samples and provides a simple yet effective manner of mining color features for object tracking. Third, by combining our OGB algorithm and our log color features, we develop a fast yet effective color-based object tracking algorithm. Numerous experiments demonstrate that our tracking algorithm is better than or not worse than some state-of-the-art tracking algorithms on some public sequences.Overall, this paper presents a novel BCD algorithm for color object tracking that achieves good results at a fast speed.     

An efficient quantum search engine on unsorted database

We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The algorithm, called factorized quantum search algorithm, presented by him can locate the desired item in an unsorted database using O( $log_4N$ ) queries to factorized oracles. But the algorithm requires that all the attribute values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the attribute values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is O( $log_4N$ ) for most cases.     

计算机组装课的发展性评价

在现今我国的计算机领域的高等教育教学和职业技术教学中,有关计算机组装、维护的课程显得尤为重要,而如何的开展好这门课程一直是广大的教育工作者们关注的主要问题.     

浅谈网络安全风险的评估方法

本文通过分析网络系统风险的概念及评价体系建设原则,针对风险评估的流程进行探讨,并就应注意的几个问题提出几点建议。以期通过本文的阐述为网络管理人员更好地制定安全策略提供有效的技术支持。     

浅析数据库数据模型及信息检索方法

本文介绍了多媒体数据库三种主要的数据模型,分析了多媒体信息的特点及对数据模型的特殊要求,论述了不同数据模型的实现途径,并提出了基于内容的信息检索的特点、体系结构和处理方法。     

A Local Semi-Implicit Level-Set Method for Interface Motion

This paper proposes and implements a novel hybrid level set method which combines the numerical efficiency of the local level set approach with the temporal stability afforded by a semi-implicit technique. By introducing an extraction/insertion algorithm into the local level set approach, we can accurately capture complicated behaviors such as interface separation and coalescence. This technique solves a well known problem when treating a semi-implicit system with spectral methods, where spurious interface movements emerge when two interfaces are close to each other. Numerical experiments show that the proposed method is stable, efficient and scales up well into three dimensional problems.     

网络教学心得

该文主要讲了网络教学中必须掌握的知识要点。     

基于DSP的磁流变阻尼器信号预处理

磁流变阻尼器是一种效率高,响应快,耗能低的智能阻尼器,在众多领域具有广泛应用前景.本文设计并实现了以硬件调理加软件调理相结合的磁流变阻尼器传感器信号预处理方案,此方案中硬件部分采用了集成开关电容滤波器MF10,软件部分采用了去极值递推均值滤波并加入线性误差补偿算法,满足了磁流变阻尼器控制器信号预处理的要求,亦可作为其它信号预处理的参考.     

智能机器人运动关节集成驱动控制器研究

根据智能机器人的控制要求,提出了机器人控制系统的顶层核心控制器和底层运动控制器的双层结构,底层与顶层基于CAN总线完成关节状态信息的上传和运动指令的下达.在此基础上,采用高速DSP、IPM功率智能模块、光电编码器、无刷直流电机等构建了机器人运动关节集成驱动控制器的硬件电路,并完成了相应软件设计.结果表明,这种集成驱动控制器简化了层间联系,提高了响应速度,增加了整体集成度,有利于运动关节的驱动控制一体化.     

Peterson算法在场消隐期传输中的应用

场消隐期作为应用电视有限资源的一部分,其开发潜力正逐渐为人们所重视.本文提出了一种新型的综合数据传输业务的单缆传输电视监控系统,将控制信号搭栽在视频信号通道上运行,并以Peterson算法和Chien氏搜索法为基础,将无线通信中常用的(15,7)BCH控制编码应用于底层的单片机级的信号传输中,同时给出了相应的软件解码方法,在优化控制信号的传输线路和解决时延问题的同时,大大提高了实时数据通信的有效性和可靠性,从而达到了利用电视信号逆程资源的目的.