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Archaeological science and computing, Page 3

Burying the Digital

Clay tablet (wikipedia) I am at Museums and the Web this week in Baltimore. I was sat next to @trinkermedia and we were talking enthusiastically about  the physical, tangible and the interactive digital (as usual). Over the last few years we have been digitising very large collections of cuneiform tablets and are mid way through developing an open source Reflectance Transformation Imaging web renderer that will allow interaction with these on mobile devices and desktops. Continue reading →

Unmanned Aerial Vehicles at Portus

Parrot AR Drone at Portus Since the start of excavations by the Portus Project in 2007, aerial photography has played an important role in the recording, analysis and presentation of the research. The ability for the archaeologist to have a bird’s-eye view of an excavation gives the opportunity to see the plan of structures, their relationships with each and alignments which are not visible at ground level. Continue reading →

Laser Scanning Results from the 2013 Portus Field School

During the 2013 excavation season I completed a number of laser scan models of the site, adding to the already completed laser scan models collected in 2012 at the Palazzo Imperiale. The main focus of the 2013 season was trialling a new scanner, the Faro Focus 3D, to see how the advancements in scanning time and accuracy could aid our recording of the site. Continue reading →

Maritime Bus

Last week the Maritime Bus came to the Avenue Campus on a University Open Day to provide an insight into maritime archaeology for prospective undergraduate students, and to give current postgraduate students training and experience in outreach activities. The Maritime Bus is the only archaeology-themed exhibition of its kind in the UK. Continue reading →

Data mining and image processing experiments on photographs from Portus

As large-scale data processing becomes easier and more affordable to everyone, so too increases the temptation to try and use new technologies and methods to reduce the amount of manual labor that usually comes with classifying and categorising big data collections. With textual data, the techniques of extracting useful information from unstructured data have already been more or less established. Continue reading →