<div class="csl-bib-body">
<div class="csl-entry">Wild, B., Verhoeven, G. J., Wieser, M., Ressl, C., Schlegel, J., Wogrin, S., Otepka-Schremmer, J., & Pfeifer, N. (2022). AUTOGRAF—AUTomated Orthorectification of GRAFfiti Photos. <i>Heritage</i>, <i>5</i>(4), 2987–3009. https://doi.org/10.3390/heritage5040155</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/135770
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dc.description.abstract
Admired and despised, created and destroyed, legal and illegal: Contemporary graffiti are polarising, and not everybody agrees to label them as cultural heritage. However, if one is among the steadily increasing number of heritage professionals and academics that value these short-lived creations, their digital documentation can be considered a part of our legacy to future generations. To document the geometric and spectral properties of a graffito, digital photographs seem to be appropriate. This also holds true when documenting an entire graffiti-scape consisting of 1000s of individual creations. However, proper photo-based digital documentation of such an entire scene comes with logistical and technical challenges, certainly if the documentation is considered the basis for further analysis of the heritage assets. One main technical challenge relates to the photographs themselves. Conventional photographs suffer from multiple image distortions and usually lack a uniform scale, which hinders the derivation of dimensions and proportions. In addition, a single graffito photograph often does not reflect the meaning and setting intended by the graffitist, as the creation is frequently shown as an isolated entity without its surrounding environment. In other words, single photographs lack the spatio-temporal context, which is often of major importance in cultural heritage studies. Here, we present AUTOGRAF, an automated and freely-available orthorectification tool which converts conventional graffiti photos into high-resolution, distortion-free, and georeferenced graffiti orthophotomaps, a metric yet visual product. AUTOGRAF was developed in the framework of INDIGO, a graffiti-centred research project. Not only do these georeferenced photos support proper analysis, but they also set the basis for placing the graffiti in their native, albeit virtual, 3D environment. An experiment showed that 95 out of 100 tested graffiti photo sets were successfully orthorectified, highlighting the proposed methodology’s potential to improve and automate one part of contemporary graffiti’s digital preservation.
en
dc.language.iso
en
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dc.publisher
MDPI
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dc.relation.ispartof
Heritage
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
graffiti
en
dc.subject
cultural heritage
en
dc.subject
orthophoto
en
dc.subject
photogrammetry
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dc.subject
street-art
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dc.subject
georeferencing
en
dc.subject
structure from motion
en
dc.title
AUTOGRAF—AUTomated Orthorectification of GRAFfiti Photos
en
dc.type
Article
en
dc.type
Artikel
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.contributor.affiliation
Ludwig Boltzmann Gesellschaft—LBI ArchPro, Austria
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dc.contributor.affiliation
Independent Researcher, Austria
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dc.contributor.affiliation
Ludwig Boltzmann Gesellschaft—LBI ArchPro, Austria