Affine hull based target representation for visual tracking

Handling appearance variations is a challenging issue in visual tracking. Existing appearance models are usually built upon a linear combination of templates. With such kind of representation, accurate visual tracking is not desirable when heavy appearance variations are in presence. Under the framework of particle filtering, we propose a novel target representation for tracking. Namely, the target candidates are represented by affine combinations of a template set, which leads to better capability in describing unseen target appearances. Additionally, in order to adapt this representation to dynamic contexts across a video sequence, a novel template update scheme is presented. Different from conventional approaches, the scheme considers both the importance of one template to a target candidate in the current frame and the recentness of the template that is kept in the template set. Comprehensive experiments show that the proposed algorithm achieves superior performances in comparison with state-of-the-art works.     

Salient video cube guided nighttime vehicle braking event detection

In nighttime driving brake lights are particularly important because they offer a warning signal to prevent potential collisions. In this work, we propose a novel visual-based approach for nighttime brake light detection using three-dimensional Nakagami imaging to analyze tail lights of vehicles in front. Rather than heuristic features, such as symmetry of taillights and appearance of the third brake light, the proposed approach extracts invariant features by modeling the scattering of brake lights, thus allowing detection to proceed in a part-based manner. Experiments from extensive datasets show that the proposed system can effectively detect vehicle braking under different lighting and traffic conditions, making it a realistic option for real-world applications.     

基于非负矩阵分解的彩色图像质量评价方法

针对稀疏表示的图像质量评价模型都基于灰度图像,缺少颜色信息,该文提出一种基于非负矩阵分解(NMF)的全参考彩色图像质量评价方法。首先,从自然彩色图像中随机采样,得到训练样本,利用非负矩阵分解,训练得到特征基矩阵,并经过Schmidt正交化,构建特征提取矩阵;其次,根据视觉显著性模型,利用最大视觉显著性和显著性差值两步骤选取视觉重要区域;最后,利用特征提取矩阵,得到低维的特征向量,并最终得到彩色图像质量评价值。实验结果表明,该文方法在LIVE, CSIQ和TID2008 3个图像质量评价库上有很好的表现。3个图像库的平均结果显示,该文方法的综合表现优于所有对比方法。这表明该文方法与主观感知有更好的关联度。     

Sample selection for visual domain adaptation via sparse coding

Visual domain adaptation has attracted much attention and has made great achievement in recent years. It deals with the problem of distribution divergence between source and target domains. Current methods mostly focus on transforming images from different domains into a common space to minimize the distribution divergence. However, there are many irrelevant source samples for target domain even after the transformation. In order to eliminate the irrelevant samples, we develop a sample selection algorithm using sparse coding theory. We do the sample selection in a common subspace of source and target data to find as many as relevant source samples. In the common subspace, data characteristics are preserved by using graph regularization. Therefore, we can select the most relevant samples for our target image classification task. Moreover, in order to build a discriminative classifier for the target domain, we use not only the common part of source and target domains learned in the common subspace but also the specific part of target domain. The algorithm can be extended to handle samples from multiple source domains. Experimental results show that our visual domain adaptation method on the image classification tasks can be very effective for the state-of-the-art datasets.     

Small-world brain functional network altered by watching 2D/3DTV

With the development of display technology, the healthy problems caused by watching 2D/3DTV have received more and more attention. This paper utilized resting-state functional magnetic resonance imaging to study the changes of small-world brain network before and after one-hour 2D/3DTV watching, and explored the brain fatigue mechanism caused by watching 2D/3DTV. We conclude that one-hour watching of 2DTV will not increase the burden of brain. On the contrary, one-hour watching of 3DTV requires the brain to regulate the efficiency of brain areas, such as temporal lobe and occipital lobe, which may explain the fact that watching 3DTV can easier cause brain fatigue than watching 2DTV.     

MapInfo与Visual Basic动态数据交换(DDE)的实现

简述了桌面地图信息系统ＭａｐＩｎｆｏ及其开发环境——ＭａｐＢａｓｉｃ的主要功能和特点;介绍了通过由源向目标发送数据,实现ＭａｐＩｎｆｏ与ＶｉｓｕａｌＢａｓｉｃ之间动态数据交换（ＤＤＥ）的方式。     

基于Visual C++的传感器稳定性测试系统设计与实现

本文基于传感器稳定性测试中存在的一些效率低等问题,开发并设计出一套Visual C++的系统.在计算机的主控器上指令编程IO数字量输出卡,完成对G5V-2继电器开关的控制切换.该系统具有网络通讯集成功能,通过TCP/IP协议,能在局域网内实时监视传感器稳定性测试,并且还能远程控制压力控制器以及调温箱,通过模拟工业现场特定环境中的压力以及温度条件等测试传感器的稳定性.     

用并口实现D/A转换器的快速测试

本文简要介绍了D/A转换原理及D/A转换器快速测试的虚拟仪器实现方案,并给出了部分关键源程序.     

基于PCI-1712高速采集卡的虚拟示波器设计

在WindowsXP操作平台下使用PCI高速采集卡,结合面向对象的可视化开发C环境VB6.0设计完成了集双通道信号采集、波形显示、波形发生、滤波、波形存储等功能为一体的虚拟示波器.系统在开发方式上采用VB6.0常用控件结合采集卡底层驱动函数与功能控件来实现对采集卡的控制功能,并运用DMA采集方式以保证传输速率.采用中值滤波法对采样信号进行数字滤波.目前,此设计已应用到兰州陆军总院骨质疏松治疗仪中的虚拟示波部分.经过反复试验,运行效果良好.