基于光流法算法的Visual Map快速建立方法

Visual Map是一个含有丰富位置信息的图像数据库,数据库中每一幅图片或图片的特征在存储时会加入相应的位置信息.室内定位的性能与Visual Map图片的数量有关.建立庞大的图片数据库能够使得定位结果更加准确,但是花费时间成本会更大.针对这个问题,本文提出了使用光流法算法来建立图片数据库Visual Map.针对光流法用于室内图像的计算会受到光线明暗不同的影响以及相机转向会产生横向偏移的问题,本文对光流法进行了改进,并使用改进后的光流法算法对摄像机采集的图像序列进行计算,得到摄像机的自身位移,从而得到每一幅图片的对应的地理位置信息.实验结果表明,利用使用光流法快速建立的Visual Map进行室内定位,误差小于1米的概率是26%,误差小于2米的概率是70%.与传统的视觉室内定位法相比,定位精度虽然略有降低,但建立图像数据库所需时间消耗大大减少.相比于视频流快速建立Visual Map方法,定位效果相当,建立Visual Map所需的设备更少,要求更加宽松.利用光流法算法快速建立Visual Map能够很好的应用于室内视觉定位系统,特别是应用于大型场所以及室内场景多变化的场所.

基于图像关键帧的Visual-Depth Map建立方法

对于室内视觉定位系统,需要在离线阶段建立Visual Map数据库用来存储图像信息,在线阶段用户通过与Visual Map数据库进行比对来完成用户位置的估计.离线阶段建立的数据库可以采用逐点采样或视频流采样的方式.但是无论何种方式,考虑到数据库中图像信息的相似性,传统方式建立的数据库中存储图像有较多冗余,导致增加了在线阶段的定位时间开销.因此,本文根据Visual Map中的相邻图像间的相似性,提出了一种基于图像关键帧的Visual-Depth Map建立方法,有效地减少了离线数据库的规模.在离线阶段,本文使用Kinect传感器同时获得图像信息和深度信息;然后,通过基于图像相似度的图像关键帧算法对原始图像序列进行筛选,得到关键帧序列,从而实现Visual-Depth Map的建立.在线阶段,用户可以直接输入查询图像与Visual-Depth Map中的图像序列进行检索匹配,找到相似度较高的匹配图像,再通过EPnP算法进行2D-3D的位姿估计,完成用户位置的计算.实验证明,本文所提方法可以在保证较高定位精度的前提下,有效减少离线数据库规模,降低在线阶段的定位时间开销.

基于Visual C++环境的MapObjects组件开发

分析了MapObjects组件的特点和功能,介绍了在VisualC++环境下基于MapObjects组件开发地理信息系统的方法,并结合一个车辆定位监控系统探讨了图层处理、实时跟踪、地理要素拾取、图层标注、交互式提示等功能的具体实现,给出了该系统的设计原理、组成、功能、主要技术特点及其应用。实践表明,系统编程体现了地图组件处理地理信息的优势和面向对象编程的灵活性。

Visualization of Disciplinary Profiles: Enhanced Science Overlay Maps

Purpose： The purpose of this study is to modernize previous work on science overlay maps by updating the underlying citation matrix, generating new clusters of scientific disciplines, enhancing visualizations, and providing more accessible means for analysts to generate their own maps Design/methodology/approach： We use the combined set of 2015 Journal Citation Reports for the Science Citation Index （n of journals = 8,778） and the Social Sciences Citation Index （n = 3,212） for a total of 11,365 journals. The set of Web of Science Categories in the Science Citation Index and the Social Sciences Citation Index increased from 224 in 2010 to 227 in 2015. Using dedicated software, a matrix of 227 × 227 cells is generated on the basis of whole-number citation counting. We normalize this matrix using the cosine function. We first develop the citing-side, cosine-normalized map using 2015 data and VOSviewer visualization with default parameter values. A routine for making overlays on the basis of the map （＂wc 15.exe＂） is available at http：//www.leydesdorff.net/wc 15/index.htm. Findings： Findings appear in the form of visuals throughout the manuscript. In Figures 1 9 we provide basemaps of science and science overlay maps for a number of companies, universities, and technologies. Research limitations： As Web of Science Categories change and/or are updated so is the need to update the routine we provide. Also, to apply the routine we provide users need access to the Web of Science. Practical implications： Visualization of science overlay maps is now more accurate and true to the 2015 Journal Citation Reports than was the case with the previous version of the routine advanced in our paper.Originality/value： The routine we advance allows users to visualize science overlay maps in VOSviewer using data from more recent Journal Citation Reports.

Visualization Analysis of Multi-Domain Access Control Policy Integration Based on Tree-Maps and Semantic Substrates

The complexity of multi-domain access control policy integration makes it difficult to understand and manage the policy conflict information. The policy information visualization technology can express the logical relation of the complex information intuitively which can effectively improve the management ability of the multi-domain policy integration. Based on the role-based access control model, this paper proposed two policy analyzing methods on the separated domain statistical information of multi-domain policy integration conflicts and the policy element levels of inter-domain and element mapping of cross-domain respectively. In addition, the corresponding visualization tool is developed. We use the tree-maps algorithm to statistically analyze quantity and type of the policy integration conflicts. On that basis, the semantic substrates algorithm is applied to concretely analyze the policy element levels of inter-domain and role and permission mapping of cross-domain. Experimental result shows tree-maps and semantic substrates can effectively analyze the conflicts of multi-domain policy integration and have a good application value.

Rate Control Algorithm of Wireless Video Based on Visual Saliency Map Model

In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.

Semi-Direct Visual Odometry and Mapping System with RGB-D Camera

In this paper a semi-direct visual odometry and mapping system is proposed with a RGB-D camera,which combines the merits of both feature based and direct based methods.The presented system directly estimates the camera motion of two consecutive RGB-D frames by minimizing the photometric error.To permit outliers and noise,a robust sensor model built upon the t-distribution and an error function mixing depth and photometric errors are used to enhance the accuracy and robustness.Local graph optimization based on key frames is used to reduce the accumulative error and refine the local map.The loop closure detection method,which combines the appearance similarity method and spatial location constraints method,increases the speed of detection.Experimental results demonstrate that the proposed approach achieves higher accuracy on the motion estimation and environment reconstruction compared to the other state-of-the-art methods. Moreover,the proposed approach works in real-time on a laptop without a GPU,which makes it attractive for robots equipped with limited computational resources.

Research on Ubiquitous Map Visualization for Ternary Space

In the era of information and communication technology (ICT) and big data, the map gradually shows a new qualitative feature of “spatiotemporal ubiquitous” with the extension of its object space, expression space and information source, which challenges the theory of cartographic visualization. This paper discusses the ubiquitous map visualization from the object content and expression form. Oriented to the ternary space, it divides the object dimension of ubiquitous map visualization and analyzes the expression characteristics of ubiquitous map visualization. Based on that, it constructs the variable system, symbol system and method system of ubiquitous map visualization. With three cases of the metro roadmap, the tag map, and the three-dimensional (3D) city map, the application of the proposed content is explained to illustrate its effectiveness. The research in this paper is expected to further enrich the theoretical basis of cartographic visualization and provide theoretical support for the expression and application of ubiquitous map visualization.

APPLICATION OF MAP AND FILE INFORMATIONVISUALIZATION SYSTEM TO COMPREHENSIVEDIVISION OF NATURAL DISASTERS- Takingthe ChangjiangValleg as an Example

ABSTRACT: This paper generalizes the makeup and forming dynamic mechanism of natural disaster systems, principles and methods of comprehensive division of natural disasters, as well as structure, function and up-build routes of map and file information visualization system (MFIVS). Taking the Changjiang(Yangtze) Valley as an example, on the basis of revealing up the integrated mechanism on the formations of its natural disasters and its distributing law, thereafter, the paper relies on the MFIVS technique, adopts two top-down and bottom-up approaches to study a comprehensive division of natural disasters. It is relatively objective and precise that the required division results include three natural disaster sections and nine natural disaster sub-sections, which can not only provide a scientific basis for utilizing natural resources and controlling natural disaster and environmental degradation, but also be illuminated to a concise, practical and effective technique on comprehensive division.

基于优化RTAB-Map的室内巡检机器人视觉导航方法

巡检机器人对室内场景进行自主导航监测时,采用视觉同时定位与地图构建(simultaneous localization and mapping,SLAM)方法构建的三维深度地图存在实时性不高、定位精度下降的问题。对此,提出了一种基于RGB-D相机和优化RTAB-Map(real time appearance based mapping)算法的巡检机器人视觉导航方法。首先,通过重新配置RTAB-Map点云更新频率,实现算法优化,构建稠密的点云地图后;采用启发式A*算法、动态窗口法(dynamic window approach,DWA)分别制定全局与局部巡检路径,通过自适应蒙特卡罗定位(adaptive Monte Carlo localization,AMCL)方法更新机器人的实时位姿信息,再将搭建好的实体巡检机器人在软件、硬件平台上完成视觉导航测试实验。结果表明:优化后的RTAB-Map算法运行时的内存占比稍有增加,但获得与真实环境一致性更高的三维深度地图,在一定程度上提高视觉导航的准确性与实用性。

Visual Information Processing Based on Qualitative Mapping

Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology realization.Visual information processing in existence,e.g.visual information processing facing to nerve calculation,visual information processing using substance shape distilling and wavelet under high yawp,ANN visual information processing and etc,are very complex in comparison.Using qualitative Mapping,this text describes the specific attributes in the course of visual information processing and the results are more brief and straightforward.So the software program of vision recognition is probably easier to realize.

一种可解释的云平台任务终止状态预测方法

基于特征选择和模型可解释方法构建可解释性强的云平台任务终止状态预测模型,该模型可视化任务/作业的静态和动态属性与终止状态之间的映射关系,进而找出负载特征与任务终止状态之间的映射机理.利用Google公开的工作负载监控日志,并加入云平台中任务的动态信息,采用沙普利加和解释(Shapley additive explain,SHAP)找出静态和动态属性对终止状态影响的重要性,利用变量重要性结合SHAP值和XGBoost模型,对任务终止状态预测模型建模后的结果进行解释,使用可视化技术呈现负载特征如何影响模型对不同任务终止状态的预测.用SHAP值绝对值的平均值衡量特征的重要性,实现任务不同终止状态特征重要性的全局可视化,根据结果筛选出对任务终止状态预测模型影响大的20个变量,作为特征筛选的依据;由可视化的结果可知,任务运行过程中,各特征的不同特征值对任务的终止状态有影响,不同特征值对终止状态的产生有不同的影响.特征选择结合模型可解释性方法运用于任务终止状态预测模型的构建流程中,可辅助构建高分类性能及易于理解的任务终止状态预测模型,通过对负载特征与任务终止状态之间映射机理的探索,可以优化云平台的调度机制.

视觉SLAM方法综述

实时定位与建图(SLAM)技术搭载特定传感器,使移动机器人在无任何环境先验条件下,在运动过程中自主建立环境模型来计算自身位姿,大幅提高其自主导航能力,以及对不同应用环境的适应性。视觉SLAM方法以相机作为外部传感器,通过采集周围环境信息来创建地图并实时估计机器人自身位姿。为此,介绍了具有代表性的经典视觉SLAM方法及与深度学习相结合的视觉SLAM方法,分析了视觉SLAM方法中采用的不同特征检测方法、后端优化、闭环检测,以及动态环境下视觉SLAM方法的应用,总结了视觉SLAM方法的问题,并探讨了视觉SLAM方法在未来的热点研究方向和发展前景。

国内生物质气化研究热点、演进与趋势分析

为客观全面地分析我国生物质气化领域的发展脉络及研究动态,以近30年关于“生物质气化”的1722篇文献作为数据源,利用知识图谱软件对发文量、机构及关键词等进行文献计量与内容分析,解析该领域的前沿热点和发展趋势。研究表明:生物质气化发文量可分为初出萌芽期、蓬勃发展期和小幅下降期;我国生物质气化研究的热点集中在拓展生物质气化原料选择范围及优化气化技术、提高气化产物效率等方面,从重产率转向重社会效益。未来我国生物质气化的研究趋势为生物质原料外扩、气化反应机理、气化反应过程和气化产物高值化利用等方向。

Bibliometric and Visualized Analysis of Cardiac Rehabilitation Research for Coronary Heart Disease Patients

Objective: This study visualizes and analyzes the current status, hotspots, and frontiers of cardiac rehabilitation for patients with Coronary Heart Disease (CHD) over the past decade (2012.01-2022.12), and explores the future development trend and research direction of the CR for CHD patients in China. Methods: Relevant literature was searched, screened and downloaded from the Web of Science (WOS) database, and bibliometric and visualization analyses were performed using CiteSpace VI software. Results: Through the search and screening of related literature, 2443 English articles were finally included. Among them, most of the Chinese publishers were mainly universities and had less connection with each other, while the foreign publishers were mainly universities and medical institutions in the United States and Europe, and had close connection with each other. The research content of Chinese scholars mainly focuses on the assessment of patients’ life and psychological status, as well as the assessment of cardiac function. Foreign research focuses on physical training assessment, disease perception, etc. Conclusion: Through visualizing relevant research with CiteSpace VI software in the form of a knowledge map, the research frontiers and trends in the field of cardiac rehabilitation for coronary heart disease patients in China and abroad can be discovered more intuitively. Compared with foreign research, the development of cardiac rehabilitation for coronary heart disease patients in China is relatively slow and insufficient, and institutions lack cooperation. In the future, China should accelerate the connection between regions in the field of cardiac rehabilitation and develop a cardiac rehabilitation model suitable for coronary heart disease patients in China with its own characteristics.

广东韶关丹霞山生态系统多样性及其空间定位

丹霞山复杂地形地貌塑造了很高的生态系统多样性和复杂的景观多样性,全面的系统分类、空间定位和生态系统类型描述对该区域的生态特征研究具有重要意义。本研究基于IUCN全球生态系统分类框架,结合植被类型和特殊地形地貌特征,对韶关丹霞山国家级自然保护区全境的生态系统类型进行研究,并利用遥感数据与实地调查数据,对各级生态系统进行空间定位和可视化制图。结果显示:(1)该保护区生态系统类型可划分为81类,包括3个I级类型、6个Ⅱ级类型、12个Ⅲ级类型、28个Ⅳ级类型和81个Ⅴ级类型;(2)除空间定位与格局分析外,特别对丹霞山的4个大类的特色生态系统进行了单独的空间展示,包括用面来展示的山顶生态系统23类和沟谷生态系统13类,用点来代表的洞穴生态系统4类,用线来代表崖壁生态系统4类。本研究关于生态系统类型的划分及空间定位,揭示了丹霞山地区的独特地形地貌特征和生态系统多样性特征,深化了丹霞山生态系统多样性和形成机制的理解,结果可为开展生态系统保护和管理提供重要的参考。

基于LIO-SAM建图和激光视觉融合定位的温室自主行走系统

为解决传统导航方案在温室内无法应对光照变化大、作物行间距窄、接收GPS信号差等问题,该研究提出了基于即时定位与地图构建技术的激光视觉融合式自主导航算法。该系统利用三维激光雷达VLP-16(Velodyne LiDAR,VLP-16)和惯性测量单元获取温室环境信息,采用基于紧耦合的雷达惯导定位建图(tightly-coupled lidar inertial odometry via smoothing and mapping,LIO-SAM)算法构建导航地图,基于轮式里程计和视觉里程计采用扩展卡尔曼滤波器算法实现局部定位,融合激光点云配准算法和自适应蒙特卡洛定位算法实现全局定位。同时,在自主行走系统应用A*算法规划全局路径和动态窗口算法规划局部路径,从而实现自主导航。试验结果表明,LIO-SAM算法构建的温室导航地图最大相对误差、最大绝对误差和均方根误差分别为9.9%、0.081和0.063 m,在温室内改进后的定位算法横向偏差小于0.020 m,纵向偏差小于0.090 m;当自主行走系统以0.15、0.30和0.50 m/s的速度运行时,横向偏差、纵向偏差和航向偏角的平均值分别小于0.120 m、0.10 m和8.5°,标准差分别小于0.070 m、0.140 m和6.6°。该导航方案满足自主行走系统在温室内高精度建图、定位和导航的需求,可为自主移动平台提供理论与技术支撑。

基于深度学习的移动机器人语义SLAM方法研究

为了给移动机器人提供细节丰富的三维语义地图,支撑机器人的精准定位,本文提出一种结合RGB-D信息与深度学习结果的机器人语义同步定位与建图方法。改进了ORB-SLAM2算法的框架,提出一种可以构建稠密点云地图的视觉同步定位与建图系统;将深度学习的目标检测算法YOLO v5与视觉同步定位与建图系统融合,反映射为三维点云语义标签,结合点云分割完成数据关联和物体模型更新,并用八叉树的地图形式存储地图信息;基于移动机器人平台,在实验室环境下开展移动机器人三维语义同步定位与建图实验,实验结果验证了本文语义同步定位与建图算法的语义信息映射、点云分割与语义信息匹配以及三维语义地图构建的有效性。