Spatiotemporal retrieval of dynamic video object trajectories in geographical scenes

Current studies on video trajectory retrieval focus on the retrieval and analysis of image content, neglecting the gap between the spatiotemporal continuity of retrieval conditions and the spatiotemporal discontinuity of multi‐camera video trajectories. In this study, we propose a method for the spatiotemporal retrieval of dynamic video object trajectories in geographic scenes. Based on the camera calibration, the proposed method organizes the scene, cameras, and trajectories, constructs the spatiotemporal constraints, and queries the trajectories using two measures: camera‐by‐camera retrieval and global trajectory retrieval. The proposed method was verified through experiments, and the results demonstrate that both measures can query trajectories effectively and reduce the spatiotemporal video review range under different spatiotemporal constraints. Furthermore, compared with camera‐by‐camera retrieval, global trajectory retrieval can reduce the spatiotemporal video review range further and return more accurate results. The proposed method may provide support for the spatial analysis and understanding of surveillance video data.     

监控视频动态目标的空间定位方法北大核心CSCD

针对监控视频动态目标的空间定位问题,本文在考虑相机畸变的前提下,对监控相机、目标像素坐标和地理场景之间的映射关系进行了研究,提出了基于数字表面模型(DSM)和基于平面约束的目标定位算法。首先,完成相机的标定,确定相机的成像模型;然后,提取畸变校正后的目标像素坐标,并通过目标定位算法计算目标的三维地理坐标;最后,进行了定位精度评定,并分析了两种定位算法的应用特点。本文的定位算法将以像素坐标定位的目标数据解析为以三维坐标定位的空间地理信息,为多摄像头的目标跟踪提供了统一的地理参考框架。     

顾及三生空间交互特征的城市空间宜居性评价——以武汉市为例

本文从三生空间功能角度出发,融合多源地理数据建立了三生空间分类指标体系,并进一步顾及空间交互特征,建立了城市空间宜居性评价体系.以武汉市为例,对武汉市中心城区的三生空间格局进行了识别,并对该区域的宜居水平进行了评价分析.结果表明:①武汉市中心城区三生空间的总体配置不均匀,空间上呈现出生活空间中心聚集、生产空间四周分散、...     

利用位置签到数据探索城市热点与商圈

众源地理数据（Crowd Sourcing Geographic Data）是指由大众采集并向大众开放共享的地理空间数据。众源位置签到数据作为众源地理数据的一种,客观真实的反映了大众日常生活行为,包含大量丰富的社会化属性信息。本文提出了一种基于众源位置签到数据的城市热点探测与商圈挖掘方法,首先对位置签到数据时空分布特性进行了研究,设计并提出了众源位置签到数据时空数据库模型;其次,提出了位置签到数据探索性空间分析方法,通过对众源位置签到数据的空间聚类分析,实现基于位置签到数据的商圈热点探测;最后,以武汉市为例,对街旁网截止2011年9月30日的众源位置签到数据进行了城市热点探测与商圈挖掘分析实验,结果表明,基于众源位置签到数据挖掘的武汉市商圈分布与城市规划商圈具有强相关性,可用于城市社会经济发展预测与区域经济规划。     

出租车轨迹数据的南京人群出行模式挖掘

针对现有出租车轨迹数据挖掘中时间序列邻近度量方法存在的问题,提出一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,进而研究城市人群出行行为的时空差异。以南京市为例,结合电子地图对出行模式的空间分布特征进行分析,证明了本文所提出的方法的有效性。实验结果表明:在空间分布上,工作日出租车出行模式按照平均出行频次由高到低排序,从城市中心向四周扩散,呈中心环状分布,出行模式区域界限较为明显,同类出行模式分布区域对应相似的功能。提出了一种基于DBSCAN算法和改进的DTW距离的时间序列聚类算法提取具有相似性出行特征的时空模式,有效地分析城市人群出行行为的时空差异。     

绝对空间定位到相对空间感知的行人导航研究趋势

相对空间比绝对空间更易于被人理解。行人导航本质是以相对于人的导航环境视觉与空间等相对语义来动态引导行人的过程,即相对导航。目前,GIS导航理论以绝对定位与空间建模为基础,没有充分理解人对相对语义的认知差异,缺乏基于相对语义的导航理论模型。首先,总结了以绝对空间定位与表达为基础的行人导航研究,提出了相对空间感知的行人导航研究新方向。然后,剖析了相对导航研究的理论研究需求,如:行人相对导航数据采集与建模、行人导航环境相对语义的提取、行人导航行为的自动感知分析、行人导航的多感官交互机制、行人导航路径选择与确认机制等。最后,展望了未来行人导航研究与重要创新的3个阶段。     

监控视频与2D地理空间数据互映射

在分析计算机视觉、摄影测量学相机模型的基础上,提出了多平面约束的监控视频与2D地理空间数据的几何互映射模型和面向互增强的内容互映射模型,并就其应用进行了介绍。针对几何互映射中存在的地面起伏对映射的影响以及监控视频空间分辨率等问题进行了分析。该模型适合于地面区域为多个平面的情况。研究表明,监控视频与2D地理空间数据可以实现一定精度下的互映射,能够满足视频监控系统与GIS的深度集成。     

Human conceptions of spaces: Implications for GIS

The way people conceptualize space is an important consideration for the design of GIS, because a better match with people's thinking is expected to lead to easier-to-use information systems. Everyday space, the basis to GIS, has been characterized in the literature as being either small-scale (from table-top to room-size spaces) or large-scale (inside-of-building spaces to city-size spaces). While this dichotomy of space is grounded in the view from psychology that people's perception of space, spatial cognition, and spatial behaviour are experience-based, it is in contrast to current GIS, which enable us to interact with large-scale spaces as though they were small-scale or manipulable. We analyse different approaches to characterizing spaces and propose a unified view in which space is based on the physical properties of manipulability, locomotion, and size of space. Within the structure of our framework, we distinguish six types of spaces: manipulable object space (smaller than the human body), non-manipulable object space (greater than the human body, but less than the size of a building), environmental space (from inside-of-building spaces to city-size spaces), geographic space (state, country, and continent-size spaces), panoramic space (spaces perceived via scanning the landscape), and map space. Such a categorization is an important part of Naive Geography, a set of theories on how people intuitively or spontaneously conceptualize geographic space and time, because it has implications for various theoretical and methodological questions concerning the design and use of spatial information tools. Of particular concern is the design of effective spatial information tools that lead to better communication.     

基于历史拓扑和描述子的时空数据模型

针对已有时空数据模型在表达时空信息上存在的问题,提出基于一个新的历史拓扑和描述子的时空数据模型STORM.STORM采用结合显式表达和隐式表达的混合型方法来表示时空信息,其中历史拓扑显式表达时空对象间的历史关联,而描述子隐式表达单个时空对象的内部属性变化以及时空对象间的空间拓扑关系.该模型可以同时表达时空信息的静态语义和动态语义,并可通过扩展的关系结构和关系代数操作进行表示和查询.     

集成多源地理大数据感知城市空间分异格局

多源地理大数据为地理现象的分布格局、相互作用及动态演化提供了前所未有的社会感知手段。城市是人类活动最为集中的区域,产生了多种地理大数据,并支持对于城市空间的理解。城市内部的分异格局是城市研究和规划所要面对的重要议题,社会感知数据提供了从"人-地-静-动"4个维度刻画城市分异格局的途径。梳理了不同类型大数据对于表达这4个维度特征的支持,并借鉴"生态位"模型,通过一个实例研究展示了集成多源数据量化城市空间分异特征的应用,最后讨论了相关的理论问题。     

Object tracking in surveillance video based on Siamese network considering geographical spatiotemporal constraints

Identifying and tracking objects in surveillance videos is an important means of mining information during surveillance. Currently, most object-tracking methods rely only on image features, which cannot accurately express the motion of the tracked object in real geographical scenes and are easily influenced by occlusion and surrounding objects having similar features. However, tracked objects, such as pedestrians and vehicles, usually move in geographical space with fixed patterns of motion, and the motion in a short time is constrained by geographical space and time, the motion trajectory is predictable, and the range of motion is limited. Therefore, based on the SiamFC object tracking framework, this study introduces geographical spatiotemporal constraints into the tracking framework and proposes the GeoSiamFC method. The objective of this is to: (1) construct the mapping relationship between geographical space and image space to solve the problem that the pixel movement within the image after perspective imaging cannot accurately express the motion of the tracked object in a real geographical scene; (2) add candidate search areas according to the predicted trajectory location to correct the tracking errors caused by the occlusion of the object; and (3) focus on the search for the range of motion of the mapped pixel within the image space according to the limited geographical range of motion of the tracked objects in a certain time to reduce the interference of similar objects within the search area. In this study, separate experiments were conducted on a common test dataset using multiple methods to deal with challenges such as occlusion and illumination changes. In addition, a robust test dataset with noise addition and luminance adjustment based on the common test dataset was used. The results show that GeoSiamFC outperforms other object-tracking methods in the common test dataset with a precision score of 0.995 and a success score of 0.756 compared with most other object-tracking algorithms under the base condition of using only shallow networks. Moreover, GeoSiamFC maintained the highest precision score (0.970) and high success score (0.734) in the more challenging robust test dataset as well. The tracking speed of 59 frames per second far exceeds the real-time requirement of 25 FPS. Geographical spatiotemporal constraints were considered to improve tracker performance while providing real-time feedback on the motion trajectory of the target in geographical space. Thus, the proposed method is suitable for real-time tracking of the motion trajectory of a target in real geographical scenes in various surveillance videos.     

An Event‐driven Spatiotemporal Data Model (E‐ST) Supporting Dynamic Expression and Simulation of Geographic Processes

The wide use of various sensors makes real‐time data acquisition possible. A new spatiotemporal data model, the Event‐driven Spatiotemporal Data Model (E‐ST), is proposed to dynamically express and simulate the spatiotemporal processes of geographic phenomena. In E‐ST, a sensor object is introduced into the model as a flexible real‐time data source. An event type that is generating and driving conditions is registered into a geographic object, so an event can not only express spatiotemporal change in a geographic object, but also drive spatiotemporal change in some geographic objects. As a dynamic GIS data model, the E‐ST has five characteristics – Temporality and Spatiality, Real‐time, Extendability, Causality, and Realizability. Described and realized in UML, a test‐case deployment demonstrating the impact of urban waterlogging on traffic confirms that a spatiotemporal change process in a geographic phenomena is expressed and simulated by this model. Summarizing this work, four directions for future research are outlined.     

基于WebGIS的平安城市视频监控系统的设计与实现

介绍了城市视频监控地理信息系统的基本内容及基于WebGIS的城市视频监控地理信息系统组成,利用SuperMap空间数据库进行城市视频监控点的空间信息和属性信息的存储、可视化查询和修改,为维护社会安全提供了有力的技术保障。     

Integrating Spatial Data Linkage and Analysis Services in a Geoportal for China Urban Research

Many geoportals are now evolving into online analytical environments, where large amounts of data and various analysis methods are integrated. These spatiotemporal data are often distributed in different databases and exist in heterogeneous forms, even when they refer to the same geospatial entities. Besides, existing open standards lack sufficient expression of the attribute semantics. Client applications or other services thus have to deal with unrelated preprocessing tasks, such as data transformation and attribute annotation, leading to potential inconsistencies. Furthermore, to build informative interfaces that guide users to quickly understand the analysis methods, an analysis service needs to explicitly model the method parameters, which are often interrelated and have rich auxiliary information. This work presents the design of the spatial data linkage and analysis services in a geoportal for China urban research. The spatial data linkage service aggregates multisource heterogeneous data into linked layers with flexible attribute mapping, providing client applications and services with a unified access as if querying a big table. The spatial analysis service incorporates parameter hierarchy and grouping by extending the standard WPS service, and data‐dependent validation in computation components. This platform can help researchers efficiently explore and analyze spatiotemporal data online.     

一种城市形态中的空间可视分析方法

空间可视分析是空间句法的重要依据,是进行城市空间形态分析的新方法。在视域的行为指导原理上,采用可视集中性的概念来进行可视分析,进而通过可视分析各参数的具体量化,包括视域面积、视线长度等,将其应用到具体的城市街道形态中,分析各参数量化大小的分布情况。研究城市形态中可视分析通过“视域法则”影响人的行为,从而潜在决定城市内有关行人等基础设施的布局情况,现实中的设施分布也证明了这种分析的正确性。以武汉市中南地区为分析实例,说明上述各过程,验证城市形态对空间设施分布的影响。     

Modeling spatiotemporal topological relationships between moving object trajectories along road networks based on region connection calculus

Considering the attempts to model spatiotemporal topological relationships between moving object trajectories, the conceptual and computational framework for moving objects along a road network has not received much attention. This paper aims to draw an improved model based on Region Connection Calculus (RCC) theory to represent the spatiotemporal topological relationships between moving object trajectories along road networks. This paper first uses a dimension reduction method based on a linear-reference transformation to model the moving object trajectories segments, and then defines new time–connection and space–connection relations between two trajectory segments. On this basis, the paper proposes an extension to the RCC-based spatiotemporal binary relationship set so that the combined semantics of the spatiotemporal predicates can be described completely. A case study was carried out using Floating Car Data in Guangzhou city. The computational results show that in a real application, the occurrence frequencies of the RCC-based binary relationships are distributed nonuniformly and the semantics of some binary relationships with the highest occurrence are coarse. Therefore, the partition of the spatiotemporal connection relations and the finer aspects of the spatiotemporal relationship model may require further research work.     

实时GIS时空数据模型

为满足动态目标与传感器等实时观测数据获取、存储、管理、分析与可视化的要求,需要发展一种新型地理信息系统—实时GIS。本文根据实时GIS中各种地理要素的特点以及存贮管理要求,提出了一种面向动态地理对象与动态过程模拟的实时GIS时空数据模型,它将时空过程、地理对象、事件、事件类型、状态、观测等相关要素整合在一个时空数据模型中。基于该模型研发了新一代实时GIS,并以四种动态地理对象（包括移动对象、原位传感器对象、视频对象和过程模拟对象）的时空数据的实时接入、存储与可视化为例,验证的模型的可行性。     

基于时空立方体的人群异常行为检测与定位

针对视频监控系统中人群异常行为检测准确率低的问题,提出了一种基于时空立方体的人群异常行为检测与定位方法。首先利用光流法计算等间距采样的特征点光流场,然后根据光流场计算特征点的运动速度、方向和方向熵3个特征量,并分别将其统计直方图投影到对应的三维立体空间中,构建描述人群行为的时空立方体特征。同时,将图像分成多个子区域,并计算各子区域的时空立方体特征;设计基于最近邻分类和支持向量机的级联分类器,完成人群异常行为的检测与定位。结果表明,该方法比现有方法能更准确地检测视频中的异常人群。     

无人机实时视频与三维地理场景融合

针对无人机视频巡查时无法获取视频要素与周围场景地理要素的空间关系等问题,本文提出了一种无人机实时视频与三维地理场景融合方法。该方法通过设置路线站点获取无人机实时巡查视频,利用高分辨率倾斜摄影模型构建三维地理场景,将视频在三维地理场景中投影,构建视频投影参数规范和无人机数据传输模型,实现无人机实时视频与三维地理场景融合展示;对无人机实景融合的应用流程进行设计,并通过具体案例进行试验验证。试验结果表明,无人机实景融合具有良好的表达效果,视频与三维地理场景融合度高且视频画面变形较小。该方法将无人机视频应用扩展至三维空间,为视频要素赋予了空间参考。