Browsing by Author "Ennis, A."

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    Evaluation Of MediaPlace: a geospatial semantic enrichment system for photographs
    (ACM, 2015-12-11) Ennis, A.; Nugent, Chris; Morrow, P.; Chen, Liming; Ioannidis, George; Stan, Alexandru
    In today's world of internet connected devices and smart phones, it has become effortless to create and consume vast amounts of information. This is particularly the case with photographs, with vast amounts being created and shared online every day. Never-the-less, it still remains a challenge to discover the "right" information for the appropriate purpose. This paper describes and discusses the testing and evaluation of the MediaPlace system with the well-known dataset YFCC-100M, which contains 48 million geospatial geotagged photographs, from Flickr produced by Yahoo. MediaPlace is a system which we have developed to automatically enrich geotagged photographs with semantic geospatial information derived from several online geospatial datasets.
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    A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs
    (Sensors, 2015-07-20) Ennis, A.; Nugent, Chris; Morrow, P.; Chen, Liming; Ioannidis, G.; Stan, A.; Rachev, P.
    With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for.
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    High-level geospatial information discovery and fusion for geocoded multimedia
    (Emerald Group Publishing Limited, 2013) Ennis, A.; Chen, Liming; Nugent, Chris; Ioannidis, George; Stan, Alexandru
    Purpose– Improvements and portability of technologies and smart devices have enabled a rapid growth in the amount of user-generated media such as photographs and videos. Whilst various media generation and management systems exist, it still remains a challenge to discover the right information, for the right purpose. This paper aims to propose an approach to reverse geocoding by cross-referencing multiple geospatial data sources to enable the enrichment of media and therefore enable better organisation and searching of the media to create an overall picture about places. Design/methodology/approach– The paper presents a system architecture that incorporates the proposed approach to aggregate several geospatial databases to enrich geo-tagged media with human readable information, which will further enable the goal of creating an overall picture about places. The approach enables the semantic information relating to point of interest. Findings– Implementation of the proposed approach shows that a single geospatial data source does not contain enough information to accurately describe the high-level geospatial information for geocoded multimedia. However, fusing several geospatial data sources together enables richer, more accurate high-level geospatial information to be tagged to the geocoded multimedia. Originality/value– The contribution in this paper shows that high-level geospatial information can be retrieved from many data sources and fused together to enrich geocoded multimedia which can facilitate better searching and retrieval of the multimedia.
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    A Service for Semantic Enrichment of Smartphone Photographs
    (Springer, 2014) Ennis, A.; Nugent, Chris; Morrow, P.; Chen, Liming; Ioannidis, George; Stan, Alexandru
    This paper describes an approach to model data extracted from several geospatial data sources based on the geo-metadata from a smartphone photograph. The model enables the geospatial data sources to be cross referenced and inferences made about the relationships between the data and the photograph. The service provided by our system takes a photograph and generates semantic geospatial enrichments that can be annotated to the photograph.
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    A System for Real-Time High-Level Geo-Information Extraction and Fusion for Geocoded Photos
    (ACM, 2013-12-02) Ennis, A.; Chen, Liming; Nugent, Chris; Ioannidis, George; Stan, Alexandru
    Improvements and portability of technologies and smart devices has enabled rapid growth in the amount of user generated media such as photographs and videos. Whilst various media generation and management systems exist it still remains a challenge to discover the "right" metadata information for the right purpose. This paper describes an approach to extract relevant geospatial information through reverse geocoding in addition to cross-referencing several public geospatial data sources. The extracted geospatial information can be used to enable enrichment of media with rich semantic geo-metadata and therefore enable improved organisation and searching of the media. Central to the system is the cross-referencing and data fusion of several public geospatial datasets to determine the most relevant Points of Interest and extract their relevant features. These relevant Points of Interest and features are subsequently used to annotate media with human readable information, leading to enriched media repositories. The system has been implemented as a client/server architecture, with a web interface for the client front end and Java for the backend server side processing. Details of the implementation are discussed. Testing in a scenario has been undertaken and a discussion of the testing technique and results is presented. The initial results show the system to be effective at fusing several public geospatial datasets and extracting relevant geo-metadata.