利用解耦光流运动场模型的双目视觉里程计位姿优化方法

针对地面移动测量系统(MMS)和无人驾驶车(AV)平台双目立体相机采集的图像序列进行实时载体位姿估计优化问题,提出利用光流运动场模型的载体位姿与图像光流矢量间关系,将光流矢量解耦为3个平移分量、3个旋转分量和一个深度分量,推导分析了解耦后单分量、组合分量误差对位姿估计的影响,利用仿真和真实数据试验,验证了不同模型下单分量、组合分量误差分离模型的有效性,并结合组合分量误差分离模型,提出了双目视觉里程计位姿估计的解耦光流运动场位姿优化算法。试验结果表明:该算法可在与初始估计几乎同等计算效率条件下,将载体横向平移平均误差由4.75%降低至2.2%,即横向平移误差平均降低了53.6%;将载体前向平移平均误差由2.2%降低至1.9%,即前向平移误差平均降低了15.4%,长时间运行累积误差率较低,能够满足低功耗高效率计算条件下的组合导航实时载体位姿估计需求。     

地图符号的艺术性设计

从艺术性设计的角度出发,主要从4个方面阐述了地图符号的设计:地图符号艺术性设计的重要意义;地图符号的分类和组织;地图符号艺术性设计的基本原则;地图符号艺术性设计的发展趋势。     

地图的视觉感受和显示效果在信息传输中的作用

本文探讨了地图信息传输过程中地图所采用的符号体系、色彩搭配、内容选取等因素对地图的视觉感受和显示效果的影响，并初步研究了地图的视觉感受和显示效果在地图信息传输中的重要作用。     

虚拟现实技术在天气预报中的应用研究

天气预报节目是服务行业最广,人数最多的节目之一。但目前的天气预报节目形式单一,数据图表、词汇枯燥呆板,专业术语过多。本文把虚拟现实技术应用于天气预报节目中,把枯燥的数据转化成逼真的场景。天气预报的三维场景生成与实时显示是构成天气预报该系统的重要部分,包括几何形体建模、纹理映射以及视觉效果处理等内容。系统利用MultiGenCreator进行建模和系统设计,基于Vega仿真软件环境开发了天气预报中的各种复杂场景特效;利用VisualC++实现了视景仿真程序。仿真结果表明,该系统较好地满足了视景仿真实时性和逼真度的要求。     

基于分层图像融合的SAR图像可视化增强方法

提出了一种基于分层图像融合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像可视化增强方法。根据SAR图像特点,通过图像灰度级分层、融合等处理,并在图像融合时加入动态范围约束条件进行求解,对SAR图像做了可视化增强处理,处理得到的图像动态范围满足显示打印等设备动态范围约束条件,且与常规方法相比能更多地保留原图细节信息。实验结果表明了本文方法的有效性。     

Oracle 8i数据库可视化检索技术及其在遥感图像信息系统中的应用

介绍了遥感图像信息系统对影像数据库的要求，提出了Oracle8i作为影像数据库管理的DBMS的技术方案，进一步说明了可视化检索技术在遥感图像信息系统中的重要性，最后，详细阐明了可视化检索技术的有关概念和工作原理。     

Combined object-based classification and manual interpretation–synergies for a quantitative assessment of parcels and biotopes

Recent technical advances in remote sensing data capture and spatial resolution lead to a widening gap between increasing data availability on the one hand and insufficient methodology for semi-automated image data processing and interpretation on the other hand. At the interface of GIS and remote sensing, object-based image analysis methodologies are one possible approach to close this gap. With this, methods from either side are integrated to use both the capabilities of information extraction from image data and the power to perform spatial analysis on derived polygon data. However, dealing with image objects from various sources and in different scales implies combining data with inconsistent boundaries. A landscape interpretation support tool (LIST) is introduced which seeks to investigate and quantify spatial relationships among image objects stemming from different sources by using the concept of spatial coincidence. Moreover, considering different categories of object fate, LIST enables a change categorization for each polygon of a time series of classifications. The application of LIST is illustrated by two case-studies, using Landsat TM and ETM as well as CIR aerial photographs: the first showing how the tool is used to perform object quantification and change analysis; the latter demonstrating how superior aggregation capabilities of the human brain can be combined with the fine spatial segmentation and classification. Possible fields of application are identified and limitations of the approach are discussed.     

Mapping the porosity of international border to pedestrian traffic: a comparative data classification approach to a study of the border region in Austria,Italy, and Slovenia

National borders play an important role in everyday life. Interest in border studies has increased with recent changes in geographical locations of the border or the fluctuation of the permeability of the border between some countries, such as in the European Union. Whether the nations are trying to increase traffic flow of the border or to implement stricter border control, having appropriate information of the border is crucial for effective policymaking.

The objective of this research was to identify areas of high porosity, or high permeability, for pedestrians along the southern national border region in Carinthia, Austria using terrain, land use, and road data along with geocomputational methods. Two unsupervised classification methods, the fuzzy K-means clustering and the Self-Organizing Map, were applied to segment the border into homogeneous zones according to topographic and infrastructural attributes. The fuzzy K-means clustering method was chosen for its ability to allow for a continuous approach to classification. With this method, an object can belong, with different degrees of membership, to multiple classes, which is a more realistic reflection of the natural world than discrete clustering, where each object can only belong to one class. However, the fuzzy K-means clustering method does have disadvantages, i.e. the user must determine the number of classes and the input parameters are required to be in continuous format. The second classification method, the Self-Organizing Map, is a type of artificial neural network and was chosen for its ability to automatically determine the number of classes and handle categorical data. The Self-Organizing Map is unique because it can transform high dimensional data into low dimensional display while preserving the topology and spatial distribution of the input parameters. The results of the two classification methods suggest that the fuzzy K-means classification is more effective than the Self-Organizing Map for this situation. However, more research is needed to determine the fit of these algorithms for particular spatial data classification tasks.

The results obtained from this research provide an insight into the permeability of the border region of Carinthia, Slovenia, and Italy to pedestrian traffic and can be potentially useful for decision making processes for tourism development and road transportation management in that region. Furthermore, the approach presented in this article can be applied to other national borders to identify zones permeable to pedestrian traffic.     

Measuring the influence of map label density on perceived complexity: a user study using eye tracking

ABSTRACT

We combine eye tracking and a questionnaire-based approach to explore the influence of label density on the perceived visual complexity of maps. We design two experiments in which participants are asked to search for the names of point features on maps and to rate the map complexity and legibility for different label densities. Specifically, we conduct a highly controlled experiment in which all the map variables except the label density are held constant (the controlled experiment). Then, we conduct a second experiment following the same protocol but using real maps as visual stimuli (the real-map experiment) to verify if the results of the controlled experiment were applicable to real maps. The results of both experiments indicate a significantly positive correlation between perceived visual complexity and label density and between the response time in visual search tasks and label density. Surprisingly, we observe a significant inverse correlation between the label density and two eye movement parameters (fixation duration and fixation frequency) between the two experiments. We discuss how the variables of real maps might have affected these eye movement parameters and why the results of the two experiments are inconsistent. Our findings suggest that eye tracking parameters are not reliable indicators of map complexity. These empirical results can be helpful to future map design and map complexity investigation.     

多源矢量空间数据可用性评估的可视分析

本文将可视分析引入到多源矢量空间数据可用性评估中,为用户提供探索发现数据可用性的环境.在论证可行性的基础上,制定了多源矢量空间数据可用性评估可视分析应遵循的基本原则.在反映多源空间数据的同时,根据用户需求确定评估内容,触发相应模型计算并可视化表达,将用户需求、人脑认知通过交互界面和计算机算法模型相结合,允许用户按照自身...