基于OpenGL的水下云台可视化实现

用于控制声纳姿态的水下云台在实际应用中需要实现可视化。将设计云台的Pro/E模型保存为STL标准三维图形文件格式,利用3D Explore软件将该STL文件转换为标准数组。通过Visual C++结合Open GL编程技术,实现了水下云台的可视化,对准确控制云台提供了帮助。     

基于OBE理念的大学“计算机公共基础”课的改革与实践

文章以面向工科专业的工程教育专业认证需求为导向,研究"计算机公共基础"课程体系,实现计算思维落地,将新工科人才培养、工程教育专业认证与创新创业教育相结合,构建满足工程教育专业认证需要,适合新工科教育发展,理论实践互动融合、竞赛及创新创业相结合的"计算机公共基础"课程教学体系。     

基于双面阵CCD的运动物体测速方法研究

针对交通工程中的测速要求,提出了一种基于双面阵CCD实现测量运动物体速度的方案,设计了测速系统的硬件平台,提出使用计算机控制两个面阵CCD对运动物体进行了动态图像检测、信号分析以及速度计算,并利用图像差分算法作为计时触发信号,提高了测速精度。通过对实验结果的分析证明文章所提出的方法行之有效。     

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.     

TD-SCDMA小区承载能力研究

TD-SCDMA小区承载能力是评估TD-SCDMA网络容量的基础,本文从上行、下行两个维度计算TDSCDMA小区承载能力,结合现网业务流量上下行配比,提出上行受限是目前影响TD-SCDMA网络容量的主要瓶颈。并通过分析造成上行受限的原因,提出增强TD-SCDMA小区上行承载能力的可选方案。     

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。