In recent years, a growing interest in the 3D digitisation of museum assets has been pushed by the evident advantages of digital copies in supporting and advancing the knowledge, preservation and promotion of historical artefacts. Realising photo-realistic and precise digital twins of medium and small-sized movable objects implies several operations, still hiring open research problems and hampering the complete automation and derivation of satisfactory results while limiting processing time. The work examines some recurrent issues and potential solutions, summing up several experiences of photogrammetric-based massive digitisation projects. In particular, the article presents some insights into three crucial aspects of the photogrammetric pipeline. The first experiments tackle the Depth of Field (DoF) problem, especially when digitising small artefacts with macro-lenses. On the processing side, two decisive and time-consuming tasks are instead investigated: background masking and point cloud editing, exploring and proposing automatic solutions for speeding up the reconstruction process.

HANDLING CRITICAL ASPECTS IN MASSIVE PHOTOGRAMMETRIC DIGITIZATION OF MUSEUM ASSETS

Farella, E. M.;Morelli, L.;Grilli, E.;Rigon, S.;Remondino, F.
2022

Abstract

In recent years, a growing interest in the 3D digitisation of museum assets has been pushed by the evident advantages of digital copies in supporting and advancing the knowledge, preservation and promotion of historical artefacts. Realising photo-realistic and precise digital twins of medium and small-sized movable objects implies several operations, still hiring open research problems and hampering the complete automation and derivation of satisfactory results while limiting processing time. The work examines some recurrent issues and potential solutions, summing up several experiences of photogrammetric-based massive digitisation projects. In particular, the article presents some insights into three crucial aspects of the photogrammetric pipeline. The first experiments tackle the Depth of Field (DoF) problem, especially when digitising small artefacts with macro-lenses. On the processing side, two decisive and time-consuming tasks are instead investigated: background masking and point cloud editing, exploring and proposing automatic solutions for speeding up the reconstruction process.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/330752.2
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