Constraint Databases and Geographic Information Systems

Constraint databases and geographic information systems share many applications. However, constraint databases can go beyond geographic information systems in efficient spatial and spatiotemporal data handling methods and in advanced applications. This survey mainly describes ways that constraint databases go beyond geographic information systems. However, the survey points out that in some areas constraint databases can learn also from geographic information systems

Knowledge discovery from trajectories

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAs a newly proliferating study area, knowledge discovery from trajectories has attracted more and more researchers from different background. However, there is, until now, no theoretical framework for researchers gaining a systematic view of the researches going on. The complexity of spatial and temporal information along with their combination is producing numerous spatio-temporal patterns. In addition, it is very probable that a pattern may have different definition and mining methodology for researchers from different background, such as Geographic Information Science, Data Mining, Database, and Computational Geometry. How to systematically define these patterns, so that the whole community can make better use of previous research? This paper is trying to tackle with this challenge by three steps. First, the input trajectory data is classified; second, taxonomy of spatio-temporal patterns is developed from data mining point of view; lastly, the spatio-temporal patterns appeared on the previous publications are discussed and put into the theoretical framework. In this way, researchers can easily find needed methodology to mining specific pattern in this framework; also the algorithms needing to be developed can be identified for further research. Under the guidance of this framework, an application to a real data set from Starkey Project is performed. Two questions are answers by applying data mining algorithms. First is where the elks would like to stay in the whole range, and the second is whether there are corridors among these regions of interest

Identifying Place Histories from Activity Traces with an Eye to Parameter Impact.

Events that happened in the past are important for understanding the ongoing processes, predicting future developments, and making informed decisions. Important and/or interesting events tend to attract many people. Some people leave traces of their attendance in the form of computer-processable data, such as records in the databases of mobile phone operators or photos on photo sharing web sites. We developed a suite of visual analytics methods for reconstructing past events from these activity traces. Our tools combine geocomputations, interactive geovisualizations, and statistical methods to enable integrated analysis of the spatial, temporal, and thematic components of the data, including numeric attributes and texts.We also support interactive investigation of the sensitivity of the analysis results to the parameters used in the computations. For this purpose, statistical summaries of computation results obtained with different combinations of parameter values are visualized in a way facilitating comparisons. We demonstrate the utility of our approach on two large real data sets, mobile phone calls in Milano during 9 days and flickr photos made on British Isles during 5 years

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Similarity, Retrieval, and Classification of Motion Capture Data

Three-dimensional motion capture data is a digital representation of the complex spatio-temporal structure of human motion. Mocap data is widely used for the synthesis of realistic computer-generated characters in data-driven computer animation and also plays an important role in motion analysis tasks such as activity recognition. Both for efficiency and cost reasons, methods for the reuse of large collections of motion clips are gaining in importance in the field of computer animation. Here, an active field of research is the application of morphing and blending techniques for the creation of new, realistic motions from prerecorded motion clips. This requires the identification and extraction of logically related motions scattered within some data set. Such content-based retrieval of motion capture data, which is a central topic of this thesis, constitutes a difficult problem due to possible spatio-temporal deformations between logically related motions. Recent approaches to motion retrieval apply techniques such as dynamic time warping, which, however, are not applicable to large data sets due to their quadratic space and time complexity. In our approach, we introduce various kinds of relational features describing boolean geometric relations between specified body points and show how these features induce a temporal segmentation of motion capture data streams. By incorporating spatio-temporal invariance into the relational features and induced segments, we are able to adopt indexing methods allowing for flexible and efficient content-based retrieval in large motion capture databases. As a further application of relational motion features, a new method for fully automatic motion classification and retrieval is presented. We introduce the concept of motion templates (MTs), by which the spatio-temporal characteristics of an entire motion class can be learned from training data, yielding an explicit, compact matrix representation. The resulting class MT has a direct, semantic interpretation, and it can be manually edited, mixed, combined with other MTs, extended, and restricted. Furthermore, a class MT exhibits the characteristic as well as the variational aspects of the underlying motion class at a semantically high level. Classification is then performed by comparing a set of precomputed class MTs with unknown motion data and labeling matching portions with the respective motion class label. Here, the crucial point is that the variational (hence uncharacteristic) motion aspects encoded in the class MT are automatically masked out in the comparison, which can be thought of as locally adaptive feature selection

Visualization and analysis of mobile phone location data

This thesis investigates the use of passively-collected data from mobile phone networks to map population movements. In Australia, as in most other developed countries, nearly all teenagers and working-age adults carry a mobile phone. When these phones communicate with the network they reveal their location to be within the coverage area of the base station antenna that received their transmission. This location data, if it were collected, could be used to derive movement information for most of the population. Such information does not currently exist. The thesis begins by investigating what information is available within a mobile phone network during normal operations. It looks at how difficult it is to extract this information, how frequently it is generated, and the spatial accuracy when it is used to locate a mobile handset. A new technique is described for estimating the location of a handset within the coverage area of a directional antenna. The theoretical investigation is supplemented by the collection of field data with a GPSequipped smart phone running custom software; by simulating the movement of Australia's mobile phones using census data and a database of base station antenna locations; and by analyzing the mobile phone billing records of an individual who elected to make his data public. Having researched the accuracy and availability of mobile phone location data, the thesis then looks at the feasibility of using it for various applications. These applications include sending alerts to people in the path of a tsunami; predicting the utilization of a new public transport route; tracking the movements of fugitives and missing persons; measuring internal migration within Australia; identifying abnormal population concentrations in real-time; and measuring the population of a region throughout the day/year. Finally, the thesis looks at techniques for visualizing the data. Existing techniques are explored, and a new one is proposed that makes use of clustered velocity vectors. This new approach can display the location, quantity, speed, and direction of large numbers of people at a point in time, and do so efficiently in terms of computational speed. The thesis concludes by summarizing the potential applications of mobile phone location data and suggesting areas of further research