基于受限移动对象当前及将来时刻检索的时空索引结构研究

在给定的空间及时间范围内,如何构建高效的时空索引结构,以实现对移动对象快速有效的检索,是实现定位服务、智能交通、数字化战争等诸多应用中所迫切需要解决的问题.本文依据移动对象的运动特点,提出了一种面向当前及将来时刻快速更新及有效检索的索引结构—PQR树.PQR树是综合PMRQuad树和R*树的结构,首先依据道路分布用PMRQuad树将移动对象的索引空间实行粗略的层分割,将所有快速移动对象与道路相关联.然后用R*树索引分布在各个子空间块内的类静止对象.实验结果表明PQR树具有良好的更新和查询性能.     

不确定移动对象的模糊时空范围查询

指出不确定性和模糊性在时空语义上的区别;提出不确定移动对象的模糊时空范围查询问题,即查询条件中时间、空间范围的外延是模糊的,无清晰的边界,而目标对象的位置不确定;用模糊集表示模糊查询条件,概率密度函数表示移动对象在各自不确定区域内的可能位置分布;给出了不确定对象关于模糊查询条件匹配度的计算方法;设计了基于α截集的无效对象排除和有效对象确认规则及查询算法.算法规则适用于任意概率密度分布.现有的确定或不确定范围查询可以看成是模糊时空范围查询的特例.通过实验验证了算法的效率,在各种参数设置下,约有30%~90%的查询结果可在不计算匹配度的情况下获得.     

移动对象数据库模型、查询语言及实时交通流分析

提出一种移动对象数据库模型——Dynamic Transportation Network Based Moving Objects Database(简称DTNMOD),并给出了DTNMOD中基于移动对象时空轨迹的网络实时动态交通流分析方法.在DTNMOD中,交通网络被表示成动态的时空网络,可以描述交通状态、拓扑结构以及交通参数随时间的变化过程;网络受限的移动对象则用网络移动点表示.DTNMOD 模型包含了完整的数据类型和查询操作的定义,因此可以在任何可扩充数据库(如PostgreSQL 或SECONDO)中实现,从而得到完整的数据库模型和查询语言.为了对相关模型的性能进行比较与分析,基于PostgreSQL 实现了一个原型系统并进行了一系列的实验.实验结果表明,DTNMOD 提供了良好的区域查询及连接查询性能.     

Efficient Querying and Animation of Periodic Spatio-Temporal Databases

We propose a representation of spatio-temporal objects with continuous and cyclic or acyclic periodic movements. We also describe an extended relational algebra query language for databases with such objects. We show that the new spatio-temporal databases are closed under the extended relational algebra queries, and each fixed relational algebra query can be evaluated in PTIME in the size of the input database.     

时空数据库移动点轨迹建模

时空数据库的移动点轨迹建模技术是近年来是时空数据库研究热点之一.本文在给定一系列时空数据库移动点的信息,找出实际应用中时间更新阈值和空间距离阈值,结合移动点时空模型和数学上线性回归的建模思想,建立一种新的支持过去、现在、未来的移动点轨迹模型,并有效地预测了移动点在某一时间阈值内,移动点的运动趋势及范围.     

Modeling Moving Objects over Multiple Granularities

This paper introduces a framework for modeling the movement of objects or individuals over multiple granularities. Granularity refers to selecting the appropriate level of detail for a task. At fine granularities, spatio-temporal information is revealed that was not previously known, such as additional locations that an individual visited or multiple visits to the same location. Conversely, moving to a coarser granularity or simpler view generalizes spatial and temporal aspects of movement allowing for an improved understanding of movement. Movement is modeled as geospatial lifelines, time-stamped records of the locations that an individual has occupied over a period of time. Depending on the desired granularity, lifelines are modeled as lifeline beads, necklaces, or more general approximations of these structures and this paper examines how different aspects of lifelines become relevant at refined or coarse granularities.     

时空数据模型研究

当前,相关定位设备及数据库技术的发展使得模拟和查询位置或形状随时间变化的移动物体成为可能。设计时空查询语言是构建移动对象数据库必不可少的步骤。本文在前人研究成果的基础上,提出了时空数据类型以及为了在移动对象数据库中进行时空查询而引入的相关操作符。     

Oporto: A Realistic Scenario Generator for Moving Objects

The spatio-temporal database research community has just started to investigate benchmarking issues. On one hand we would rather have a benchmark that is representative of real world applications, in order to verify the expressiveness of proposed models. On the other hand, we would like a benchmark that offers a sizeable workload of data and query sets, which could obviously stress the strengths and weaknesses of a broad range of data access methods. This paper offers a framework for a spatio-temporal data sets generator, a first step towards a full benchmark for the large real world application field of smoothly moving objects with few or no restrictions in motion. The driving application is the modeling of fishing ships where the ships go in the direction of the most attractive shoals of fish while trying to avoid storm areas. Shoals are themselves attracted by plankton areas. Ships are moving points; plankton or storm areas are regions with fixed center but moving shape; and shoals are moving regions. The specification is written in such a way that the users can easily adjust generation model parameters.     

一种车辆移动对象相似轨迹查询算法

车辆移动对象的相似轨迹查询问题是当前移动对象数据管理研究中的一个热点,可以应用在车辆缉查防控、出行规律分析及城市道路规划等诸多领域.当前,随着车辆移动对象监测手段的不断丰富,车辆移动对象数据逐渐表现出流式不间断产生、数据量急剧增大的特征.现有的移动对象相似轨迹查询方法在面对具有上述特征的车辆移动对象数据时在查询正确性和查询效率方面暴露出诸多问题.论文针对这种大规模车辆移动对象数据流下的相似轨迹查询问题,提出一种基于双阈值支持度的车辆移动对象相似轨迹查询算法,该算法通过对车辆移动对象数据的预处理来减少查询中涉及的移动对象数据量,以提高移动对象相似轨迹查询的效率,同时保证查询正确性.实验表明,该文提出的算法,在保障正确查询相似轨迹的前提下,效率比传统相似轨迹查询算法提高很多.     

一种移动物体时空轨迹聚类的相似性度量方法

针对利用最小包围盒(MBB)压缩的移动物体时空轨迹,为了能对其进行有效地聚类,提出了一个基于盒内数据点密度的轨迹间相似性度量公式.首先,把两条轨迹的相似性度量转化为两条轨迹上有时间交叠的MBB之间的相似性度量,这在很大程度上减少了数据存储量.其次,分析两条轨迹上有时间交叠的MBB之间影响相似性的因素:时间持续、空间距离和盒内数据点的密度.剖析这3个因素对轨迹相似性的影响作用,提出了利用MBB压缩的移动物体时空轨迹相似性度量公式.实验证明采用本公式对移动物体时空轨迹进行聚类,可以提高聚类结果有效性指标Dunn的值.     

Indexing the Trajectories of Moving Objects in Networks*

The management of moving objects has been intensively studied in recent years. A wide and increasing range of database applications has to deal with spatial objects whose position changes continuously over time, called moving objects. The main interest of these applications is to efficiently store and query the positions of these continuously moving objects. To achieve this goal, index structures are required. The main proposals of index structures for moving objects deal with unconstrained 2-dimensional movement. Constrained movement is a special and a very important case of object movement. For example, cars move in roads and trains in railroads. In this paper we propose a new index structure for moving objects on networks, the MON-Tree. We describe two network models that can be indexed by the MON-Tree. The first model is edge oriented, i.e., the network consists of nodes and edges and there is a polyline associated to each edge. The second one is more suitable for transportation networks and is route oriented, i.e., the network consists of routes and junctions. In this model, a polyline also serves as a representation of the routes. We propose the index in terms of the basic algorithms for insertion and querying. We test our proposal in an extensive experimental evaluation with generated data sets using as underlying networks the roads of Germany. In our tests, the MON-Tree shows good scalabiliy and outperforms the competing index structures in updating (index creation) as well as in querying.*This work was partially supported by a grant Gu 293/8–l from the Deutsche Forschungsgemeinschaft (DFG), project Datenbanken für bewegte Objekte (Databases for Moving Objects).     

受限网络移动对象不确定性轨迹的查询

针对移动对象轨迹的内在不确定性及其导致的查询精度较低的问题,将已有移动对象的空间轨迹不确定性模型应用于网络移动对象的轨迹表示中。在此基础上,将概率查询方法运用到受限网络移动对象的不确定轨迹查询中,提出移动对象轨迹的不确定性点查询和概率范围查询方法。实验结果表明,该方法具有较高的查询效率。     

An Event-Based Approach to Spatio-Temporal Data Modeling in Land Subdivision Systems

The spatio-temporal database for a collaborative decision making system supporting land subdivision is event-driven. Both various states of spatial objects and the events causing the objects change need to be recorded and manipulated in the database. To achieve this, the authors analyzed the characteristics of events in land subdivision process and studied how events affect the states of spatial objects. An event-based approach was proposed to develop the spatio-temporal data model for the GIS-based computer-supported collaborative work (CSCW) land subdivision system. A formal specification of event and its operators was introduced for describing the execution of events and their sequence. The spatio-overlap and time-meet constraints between parent-child parcels are proposed to represent the linkage between different states of land parcels. With this approach, events and the causal relations between events and states can be recorded and managed in the spatio-temporal database in a land subdivision system. In addition, a new way for simulating system work-flow is also suggested.     

不确定移动对象概率Skyline集的查询更新

Skyline查询的研究已从传统的静态Skyline操作延伸到动态的、不确定数据集上的Skyline查询和计算上。研究了移动环境下,查询点位置固定、目标点处于运动状态并且位置不确定情况下的连续概率Skyline计算问题。这个过程中,移动对象与查询对象之间的距离随时间不断变化。移动对象由于其运动状态导致位置无法精确定位,因此移动对象之间的支配关系只能采用概率形式表示,且随时间不断变化。给出了移动对象间的支配概率的定义,以及移动对象Skyline概率的定义,并定义了触发事件来记录对象支配概率发生变化的时刻,实现概率Skyline计算的连续跟踪和动态更新。提出了基于事件触发的连续概率Skyline查询算法(event triggered continuous probabilistic Skyline query for uncertain moving object,U-ECPS),对移动环境下的Skyline集进行连续查询和更新。大量的实验结果验证了U-ECPS算法的有效性。     

Modeling and Retrieval of Moving Objects

This paper presents a symbolic formalism for modeling and retrieving video data via the moving objects contained in the video images. The model integrates the representations of individual moving objects in a scene with the time-varying relationships between them by incorporating both the notions of object tracks and temporal sequences of PIRs (projection interval relationships). The model is supported by a set of operations which form the basis of a moving object algebra. This algebra allows one to retrieve scenes and information from scenes by specifying both spatial and temporal properties of the objects involved. It also provides operations to create new scenes from existing ones. A prototype implementation is described which allows queries to be specified either via an animation sketch or using the moving object algebra.     

Conceptual Modeling and Querying in Multimedia Databases

In this paper, we discuss some design principles that will aid in the design and querying of multimedia databases. We use an object-relational data model and argue that multimedia objects should normally have a special attribute called core which stores the real object itself in contrast to the abstraction which is reflected in the rest of the attributes. We present an extension to the ER Diagram that takes advantage of the core notion to facilitate design of multimedia databases. We discuss some desirable features in a query language for multimedia databases: simplifications like the use of path expressions and implicit use of functions (methods) as attributes, and explicit specification of the display layout and format either at the data definition level or query specification level. To materialize this last feature, we propose a display specification extension to SQL (SQL+D) that we have implemented.     

Reporting Leaders and Followers among Trajectories of Moving Point Objects

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern ‘one object is leading others’, which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.

一种基于数据融合和方法融合的时空综合预测算法

时空数据挖掘是数据挖掘中的重要研究内容,其中时空预测的应用领域最为广泛.针对目前时空预测方法中的不足,提出了一种基于数据融合和方法融合的时空综合预测算法.该方法首先采用统计学原理对目标对象本身的时序进行预测;然后通过神经网络解算相邻对象的空间影响,继而对混合数据序列使用时空自回归预测模型;最后使用线性回归将单个的时间预测、空间预测和时空预测有效地融合在一起,得到综合预测结果.应用该方法预测铁路客流,突破了传统铁路客流预测方法的局限,实验结果表明了算法的有效性.     

Continuous K-Nearest Neighbor Query for Moving Objects with Uncertain Velocity

One of the most important queries in spatio-temporal databases that aim at managing moving objects efficiently is the continuous K-nearest neighbor (CKNN) query. A CKNN query is to retrieve the K-nearest neighbors (KNNs) of a moving user at each time instant within a user-given time interval [t _s , t _e ]. In this paper, we investigate how to process a CKNN query efficiently. Different from the previous related works, our work relieves the past assumption, that an object moves with a fixed velocity, by allowing that the velocity of the object can vary within a known range. Due to the introduction of this uncertainty on the velocity of each object, processing a CKNN query becomes much more complicated. We will discuss the complications incurred by this uncertainty and propose a cost-effective P² KNN algorithm to find the objects that could be the KNNs at each time instant within the given query time interval. Besides, a probability-based model is designed to quantify the possibility of each object being one of the KNNs. Comprehensive experiments demonstrate the efficiency and the effectiveness of the proposed approach.

一种基于码本模型的运动目标检测算法

提出一种基于背景码本模型的视频图像中运动目标的检测算法。该算法利用归一化的Mann-Whitney秩和统计量自适应调整判决阈值,使用Mean Shift进行码本中码字和方差的更新,实现在检测过程中同时更新码本模型适应图像背景的变化。不同背景条件下的实验结果表明该算法利用Mann-Whitney秩和统计量的分布无关性,提高了运动目标检测精度。 。