Automatic semantic analysis of 3D content in digital repositories

Project Details


The increasing popularity of 3D technologies in 2014 was clearly having an impact on the amount of content that is being produced by users of these technologies. Witnessing the explosion of content such as images, music and videos available on the web, it was not difficult to predict that 3D would be the next type of content to undergo this effect. The research community was taking action to ensure 3D content can be stored and managed in databases or repositories in order to be accessible to a wide variety of users.

Nevertheless, searching for 3D content in these repositories was not an easy task. The main problem was that although a digital 3D representation of a physical object is a more accurate representation, the way that the information is stored means that automated solutions for understanding what the content represents was an unsolved challenge.

To address this problem, the research community had created ways to tag or 'attach' additional information to the 3D content, as is done with 2D images, to support the computer's understanding of what the 3D content represents. However, this process was slow as it relied on mostly manual or semi-automatic techniques.

The research project would take these basic techniques forward by researching state of the art mechanisms to automate the enrichment of 3D content.

This project aimed to demonstrate the use of 3D technologies for documenting and analysing shape in the cultural heritage domain. This was done by focusing on Cultural Heritage artefacts, in particular Regency architectural ornamental artefacts, to understand how the shape of an artefact might provide us with information about it (e.g. its origin, artistic style, production methods).

It was at the time very challenging to infer this high level information automatically. The project would thus combine expertise in shape analysis, the semantic web and Cultural Heritage in order to develop innovative techniques to automatically understand what the 3D content might represent. This process was referred to as "automatic semantic enrichment" and would allow the 3D content to be linked to a vast amount of information and knowledge which will facilitate making connections with other pieces of information.

Key findings

As a result of this project, searching for the most relevant item of 3D content amongst the petabytes of information stored in the database would be considerably improved. In turn, this would improve the availability and use of 3D content for different purposes. For instance, the project demonstrated how the research can support the restoration of historical buildings.


Karina Rodriguez Echavarria and Ran Song (2015). 'Studying Shape Semantics of an Architectural Moulding Collection: Classifying Style Based on Shape Analysis Methods.' In Proceedings of the 2nd International Congress on Digital Heritage 2015. Granada, Spain.
Best paper award in the Analysis and Interpretation track
Effective start/end date1/08/1431/05/16


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