Research Areas

Cultural Heritage Technologies’ research line aims at fostering interdisciplinary collaborations in frontiers projects that seek to cross the boundaries of traditional research in Cultural heritage, and Digital Humanities at large.

The line supports innovative ideas and approaches that require truly multi- and trans-disciplinary teams and looks into ways in which technology can expand the scope of research in cultural heritage and humanities. It capitalises on IIT's renowned strengths in 3D digitisation and retrieval, machine learning and molecular and nano-materials sciences, and it brings together the work being done in these areas. 

The Center for Cultural Heritage Technologies currently focuses on three broad research areas, drawing from well-established competencies and expertise available at IIT. 


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3D Digitisation and Retrieval

The Digitisation domain mainly focuses on the development of next generation technologies for 3D scanning of artefacts through the introduction of advanced computer vision and signal processing techniques.

The Information Retrieval domain mainly focuses on the development of search methods to provide adequate access to the large amount of digitised artefacts that increase rapidly with the advent of low-cost 3D scanning.


Machine Learning

The digital documentation of cultural heritage (CH) often requires the development of methods to infer structure and extract patterns from data. Machine Learning research at the CCHT mainly focuses on the development of innovative methods for extracting information from cultural heritage datasets; temporal understanding of multimodal-data and for predicting of smart material properties.



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Characterisation of Material Culture and its Protection

The area of characterisation deals with the use of non-destructive methods (i.e. with no sampling) that enable the analysis of different kind of objects maintaining their integrity.

The research of the group deals with the development of custom-based preservation solutions related to the structure (chemical composition and shape) of the artefact by sensing its current deterioration state.