Geo-referenced Media Research Articles

Comparing digital traces of modern travellers to journeys of two 18th-19th century British poets

The growth of interest in georeferenced media brings with it a wealth of possibilities for exploring digital media, and importantly, for advancing research concerned with domain driven research questions. In this paper, we compare previous work, which extracted and analysed the spatial traces of two 18th-19th century poets in the English Lake District with modern data digital traces in the form of Flickr images. We explore the semantics of the modern day data through use of Latent Dirichlet Allocation, and analyse the extent to which modern day tourism mimics (or indeed follows) the foundations laid by Samuel Coleridge and Thomas Gray. Our results show that tourists, just like the poets, describe mountain landscapes from below and visit popular locations commonly perceived as beautiful.

A virtual globe tool for searching and visualizing geo-referenced media resources in social networks

The current collaborative context and resource sharing that drives Web 2.0 is gaining importance within academia and industry, which is stimulating the development of new techniques for content retrieval, sharing and analysis over user-generated media content. This poses new challenges and research opportunities in spatial-based discovery media resources over varied sources, since location context is being increasingly supported in most of these social networks and services. In this paper, we present a virtual globe tool for searching and visualizing geo-referenced media resources. Our approach is based on the integration of search technologies, description languages for annotating collections of geo-referenced media resources and visualization techniques. The combination of these techniques is materialized in a virtual globe-based tool to facilitate searching and presentation of geo-referenced media resources available in different social networks.

Research and applications on georeferenced multimedia: a survey

In recent years, the emergence of georeferenced media, like geotagged photos, on the Internet has opened up a new world of possibilities for geographic related research and applications. Despite of its short history, georeferenced media has been attracting attentions from several major research communities of Computer Vision, Multimedia, Digital Libraries and KDD. This paper provides a comprehensive survey on recent research and applications on online georeferenced media. Specifically, the survey focuses on four aspects: (1) organizing and browsing georeferenced media resources, (2) mining semantic/social knowledge from georeferenced media, (3) learning landmarks in the world, and (4) estimating geographic location of a photo. Furthermore, based on the current technical achievements, open research issues and challenges are identified, and directions that can lead to compelling applications are suggested.

Relevance ranking in georeferenced video search

The rapid adoption and deployment of ubiquitous video cameras has led to the collection of voluminous amounts of media data. However, indexing and searching of large video databases remain a very challenging task. Recently, some recorded video data are automatically annotated with meta-data collected from various sensors such as Global Positioning System (GPS) and compass devices. In our earlier work, we proposed the notion of a viewable scene model derived from the fusion of location and direction sensor information with a video stream. Such georeferenced media streams are useful in many applications and, very importantly, they can effectively be searched via their meta-data on a large scale. Consequently, search by geo-properties complements traditional content-based retrieval methods. The result of a georeferenced video query will in general consist of a number of video segments that satisfy the query conditions, but with more or less relevance. For example, a building of interest may appear in a video segment, but may only be visible in a corner. Therefore, an essential and integral part of a video query is the ranking of the result set according to the relevance of each clip. An effective result ranking is even more important for video than it is for text search, since the browsing of results can only be achieved by viewing each clip, which is very time consuming. In this study, we investigate and present three ranking algorithms that use spatial and temporal properties of georeferenced videos to effectively rank search results. To allow our techniques to scale to large video databases, we further introduce a histogram-based approach that allows fast online computations. An experimental evaluation demonstrates the utility of the proposed methods.

Workshop on geographic information retrieval held at SIGIR'06

August 2006 saw the third in a series of workshops held to discuss the state of the art in Geographic Information Retrieval held in conjunction with SIGIR'06. The original call for papers for the workshop suggested the workshop should discuss further progress within the field and potential future research strands. Topics considered relevant for the workshop included the following:• architectures for geographic search engines;• spatial indexing of documents and other media resources;• extraction of geographical context from documents and geo-datasets;• geographical annotation techniques for geo-referenced media;• design, construction, maintenance and access methods for geographical ontologies, gazetteers and geographical thesauri;• geographical query interfaces for the web and geo-spatial libraries;• visualising the results of geographic searches; and• relevance ranking for geographical search.