Abstract
Graffiti are polarising. Some consider them vandalism, others part of our cultural heritage. If we consider graffiti to be part of our cultural heritage, we should also treat them as such. However, long-term and detailed graffiti documentation initiatives are sparse, so many of the existing archives with graffiti records are biased and incomplete. In addition, graffiti records usually suffer from decontextualisation, that is the lack of environmental information (be it spatially, temporally, but also smell and weather conditions). This means that graffiti documentation might not reflect the intended setting or meaning by the creator. INDIGO, a graffiti-centred academic project, largely overcomes the issue of decontextualisation by designing and implementing photogrammetric engineering approaches that support the ongoing documentation of an extensive graffiti-scape. The latter is situated along the Donaukanal, Vienna’s central waterway and one of the most prominent graffiti hotspots worldwide. One innovation developed in the framework of INDIGO is a freely available Metashape add-on called AUTOGRAF. AUTOGRAF employs photogrammetric computer vision techniques to automatically create ortophotographs from all photographed graffiti. Orthophotographs or orthophotomaps are distortion-free images, combining photographs’ visual qualities with characteristics of maps. They allow embedding the graffiti in their native, albeit virtual, 3D environment and can thus largely overcome decontextualisation.
In this contribution, we showcase the significant advantages of orthophotomaps over conventional photographs and introduce the AUTOGRAF-based workflow that allows the automated derivation of graffiti orthophotos. INDIGO will use this tailor-made tool to enable graffiti analysis in unprecedented detail by mapping and displaying graffiti in their original setting along the Donaukanal.