谈融信·正天时代广场规划建筑设计

以商业地产项目作为设计对象,抛纷繁多样的建筑风格,以理性分析为基础,寻求建筑创作的契机,以实际参与的项目为例,总结了经过SWOT分析,如何在建筑的实用性及美感上解决诸多问题,以期为当前的创作实践提供参考。     

红外双波段目标模拟器的国内外发展现状

介绍了红外双波段目标模拟器在国内外的发展情况,从双波段目标模拟器的工作原理入手,重点论述了双波段景象生成器、双波段目标模拟器的内部结构设计以及系统的准直和图像的配准几个方面的技术水平,对比了我国现阶段发展的不足,讨论了发展方向和前景。     

一种基于边缘匹配的前视红外目标识别算法

红外目标识别是影响精确制导武器命中精度的重要因素。针对因基准图与实时图存在差异导致模板匹配性能下降的问题,提出了一种基于边缘匹配的前视红外（FLIR）目标识别算法。在模板匹配的基础上,利用目标的邻域信息排除虚警,计算基于匹配代价矩阵的匹配置信度对候选匹配点进行排序,利用前面连续多帧图像的识别结果为当前帧识别提供信息,从而提高目标识别的准确性和鲁棒性。在2组不同目标类型的红外视频序列上所做的实验表明,该算法具有较好的识别性能。     

Fast accessing Web3D contents using lightweight progressive meshes

Accessing Web3D contents is relatively slow through Internet under limited bandwidth. Preprocessing of 3D models can certainly alleviate the problem, such as 3D compression and progressive meshes (PM). But none of them considers the similarity between components of a 3D model, so that we could take advantage of this to further improve the efficiency. This paper proposes a similarity‐aware data reduction method together with PM, called lightweight progressive meshes (LPM). LPM aims to excavate similar components in a 3D model, generates PM representation of each component left after removing redundant components, and organizes all the processed data using a structure called lightweight scene graph. The proposed LPM possesses four significant advantages. First, it can minimize the file size of 3D model dramatically without almost any precision loss. Because of this, minimal data is delivered. Second, PM enables the delivery to be progressive, so called streaming. Third, when rendering at client side, due to lightweight scene graph, decompression is not necessary and instanced rendering is fully exerted. Fourth, it is extremely efficient and effective under very limited bandwidth, especially when delivering large 3D scenes. Performance on real data justifies the effectiveness of our LPM, which improves the state‐of‐the‐art in accessing Web3D contents. Copyright © 2015 John Wiley & Sons, Ltd.     

虚拟现实中数据库建模

为了更好地存储和使用虚拟现实中的场景数据,提出了一种用关系数据库方式对虚拟现实中场景数据进行建模的方法．采用该方法,比其他建模方法更加规则地表示了场景数据;提高了三维数据的重用性;增强了对三维场景的可维护性;大大扩展了对特定三维数据的应用;更加合理地存储了二维控制台与虚拟场景交互的数据．该方法也为三维场景数据的优化和格式转化提供了一种途径．     

基于特征地图的改进回环检测算法

为提高移动机器人回环检测模块的准确率和实时性,提出一种基于特征地图的改进回环检测算法。在传 统模型的基础上,对关键帧的特征点进行筛选,选取高效特征点构建特征地图,利用视觉字典树对特征地图和关键 帧进行场景描述;对词袋模型进行改进,将场景分割用在图像信息的提取和特征聚类上;建立基于分层K++均值的 视觉字典树,得到改进的基于分层金字塔TF-IDF(term frequency–inverse document frequency)的匹配方法。实验结果 证明：相比FAB-MAP(fast appearance-based mapping)和RGB-D SLAM v2,改进算法在特征点规模、实时性、召回 率方面性能更优。     

基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

基于混合远景和近景区域暗通道算法的图像去雾研究

为了提高图像去雾效果,提出混合远景和近景区域暗通道算法。首先建立远景和近景区域暗通道,为近景区域最小值通道和远景区域最小值通道之和,不同区域设置不同的调节系数;接着估计大气光值,通过混合暗通道远景区域的前50个像素点颜色值的平均值获得,增设校正系数;然后导向滤波,采用自适应滑动窗口优化透射率;最后给出了算法流程。实验仿真显示所提算法去雾图像视觉效果较好,定量分析指标对比度、可见边对比度值较优。     

A Character Flow Framework for Multi-Oriented Scene Text Detection

Scene text detection plays a significant role in various applications,such as object recognition,document management,and visual navigation.The instance segmentation based method has been mostly used in existing research due to its advantages in dealing with multi-oriented texts.However,a large number of non-text pixels exist in the labels during the model training,leading to text mis-segmentation.In this paper,we propose a novel multi-oriented scene text detection framework,which includes two main modules:character instance segmentation (one instance corresponds to one character),and character flow construction (one character flow corresponds to one word).We use feature pyramid network(FPN) to predict character and non-character instances with arbitrary directions.A joint network of FPN and bidirectional long short-term memory (BLSTM) is developed to explore the context information among isolated characters,which are finally grouped into character flows.Extensive experiments are conducted on ICDAR2013,ICDAR2015,MSRA-TD500 and MLT datasets to demonstrate the effectiveness of our approach.The F-measures are 92.62％,88.02％,83.69％ and 77.81％,respectively.