GCH 2016 - Eurographics Workshop on Graphics and Cultural Heritage
https://diglib.eg.org:443/handle/10.2312/2630933
ISBN 978-3-03868-011-62024-03-29T13:12:07ZInterdisciplinary Dialogue Towards an Enhanced Understanding of Optical Techniques for Recording Material Cultural Heritage - Results of a COST Action
https://diglib.eg.org:443/handle/10.2312/gch20161412
Interdisciplinary Dialogue Towards an Enhanced Understanding of Optical Techniques for Recording Material Cultural Heritage - Results of a COST Action
Boochs, Frank; Bentkowska-Kafel, Anna; Wefers, Stefanie
Chiara Eva Catalano and Livio De Luca
The COST Transdomain Action TD1201, Colour and Space in Cultural Heritage [COSb], 2012-2016, contributes to the conservation and preservation of cultural heritage (CH) by enhancing shared understanding, between experts from various disciplines, of the spectral and spatial recording of physical CH objects. Optimal recording, adapted to the requirements of a CH application, should involve experts from multiple disciplines and industries. Such an interdisciplinary approach is necessary "in order to protect, preserve, analyze, understand, model, virtually reproduce, document and publish important CH in Europe and beyond" [COSa]. In order to fulfil this goal, experts from 28 European countries entered into a multidisciplinary dialogue trying to establish a common understanding of spatial and spectral recording techniques best suited for particular CH applications. Several COSCH groups worked on the characterisation of spatial and spectral recording techniques; the use of algorithms and processing chains; and requirements of analysis, restoration and visualisation of CH surfaces and objects. A range of possible applications of optical techniques, now available to recording and examination of CH objects, have been tested through six COSCH case studies [BKM17]. These projects have exposed the challenges of common understanding of the processes involved, and differences in disciplinary research needs and methods. A number of issues have been identified, sometimes as basic as lack of common specialist terminology and relevant technical standards. The complexity of the field became apparent in the course of designing COSCHKR, ontological knowledge representation, which employs semantic technologies. After four years of interdisciplinary dialogue, COSCH leaves a legacy that will help the dialogue to continue, technology to develop, and specialist training to better respond to the actual needs of the interdisciplinary CH research communities.
2016-01-01T00:00:00Z3D Object Spatial- consistent Texture Maps Appropriate for 2D Image Processing
https://diglib.eg.org:443/handle/10.2312/gch20161411
3D Object Spatial- consistent Texture Maps Appropriate for 2D Image Processing
Ioannakis, George; Koutsoudis, Anestis; Chamzas, Christos
Chiara Eva Catalano and Livio De Luca
The aim of this work is to generate a spatial-consistent UV maps of a 3D object's texture suitable for 2D image processing algorithms. An approach to produce such a fully spatially consistent UV mapping suitable for image processing based on the planar parameterisation of the mesh is presented. The mesh of a 3D model is parametrised onto a unit square 2D plane using computational conformal geometry techniques. The proposed method is genus independent, due to an iterative 3D mesh cutting procedure. The selection of the initial seed vertex for the mesh-cut is not essential for the parameterisation of the geometry, however it affects heavily the appearance of the obtained texture map. In this work we attempt to determine such a seed vertex, in order the UV map to be suitable for image processing. Having the texture of a 3D model depicted on a spatially continuous two dimensional structure enables us to efficiently apply well known image processing based techniques and algorithms. Our method is applied on a 3D digital replica of an ancient Greek Lekythos vessel.
2016-01-01T00:00:00ZToward a Multimodal Photogrammetric Acquisition and Processing Methodology for Monitoring Conservation and Restoration Studies
https://diglib.eg.org:443/handle/10.2312/gch20161409
Toward a Multimodal Photogrammetric Acquisition and Processing Methodology for Monitoring Conservation and Restoration Studies
Pamart, Anthony; Guillon, Odile; Vallet, Jean-Marc; Luca, Livio De
Chiara Eva Catalano and Livio De Luca
Close-range photogrammetry is nowadays a common technique applied to acquire 3D data on Cultural Heritage (CH) artifacts. Image-based modeling are indeed providing useful resources for the documentation and the conservation but it is also set more recently as a monitoring tool that could help the decision making in term of restoration. The 3D footprint restitutes as a point cloud, the appearance according to a definite spatial resolution and at a given time, the visible surface of an artifact. Nevertheless, different techniques of scientific imaging are also used to obtain complementary information. This paper explores a multimodal approach of the photogrammetric survey and data processing to reach a multidimensional data integration (i.e. spatial, temporal and, or spectral).
2016-01-01T00:00:00ZAccelerating Point Cloud Cleaning
https://diglib.eg.org:443/handle/10.2312/gch20161410
Accelerating Point Cloud Cleaning
Mulder, Rickert L.; Marais, Patrick
Chiara Eva Catalano and Livio De Luca
A laser scanning campaign to capture the geometry of a large heritage site can produce thousands of high resolution range scans. These must be cleaned to remove noise and artefacts. To accelerate the cleaning task, we can i) reduce the time required for batch-processing tasks, ii) reduce user interaction time, or iii) replace interactive tasks with more efficient automated algorithms. We present a point cloud cleaning framework that attempts to improve each of these aspects. First, we present a novel system architecture targeted point cloud segmentation. This architecture represents 'layers' of related points in a way that greatly reduces memory consumption and provides efficient set operations between layers. These set operations (union, difference, intersection) allow the creation of new layers which aid in the segmentation task. Next, we introduce roll-corrected 3D camera navigation that allows a user to look around freely while reducing disorientation. A user study showed that this camera mode significantly reduces a userĀ“s navigation time between locations in a large point cloud thus accelerating point selection operations. Finally, we show how boosted random forests can be trained interactively, per scan, to assist users in a point cleaning task. To achieve interactivity, we sub-sample the training data on the fly and use efficient features adapted to the properties of range scans. Training and classification required 8-9s for point clouds up to 11 million points. Tests showed that a simple user-selected seed allowed walls to be recovered from tree and bush overgrowth with up to 92% accuracy (f-score). A preliminary user study showed that overall task time performance was improved. The study could however not confirm this result as statistically significant with 19 users. These results are, however, promising and suggest that even larger performance improvements are likely with more sophisticated features or the use of colour range images, which are now commonplace.
2016-01-01T00:00:00Z