No abstract

The technological advance of sensors is producing an exponential size growth of the data coming from 3D scanning and digital photography. The production of digital 3D models consisting of tens or even hundreds of millions of triangles is quite easy nowadays; at the same time, using high-resolution digital cameras it is also straightforward to produce a set of pictures of the same real object totalling more than 50M Pixel.The problem is how to manage all this data to produce 3D models that could fit the interactive rendering constraints. A common approach is to go for mesh parametrization and texture synthesis, but finding a parametrization for such large meshes and managing such large textures can be prohibitive. Moreover, digital photo sampling produces highly redundant data; this redundancy should be eliminated while mapping to the 3D model but, at the same time, should also be efficiently used to improve the sampled data coherence and the appearance representation accuracy.In this paper we present an approach where a multivariate blending function weights all the available pixel data with respect to geometric, topological and colorimetric criteria. The blending approach proposed is efficient, since it mostly works independently on each image, and can be easily extended to include other image quality estimators. The resulting weighted pixels are then selectively mapped on the geometry, preferably by adopting a multiresolution per-vertex encoding to make profitable use of all the data available and to avoid the texture size bottleneck. Some practical examples on complex datasets are presented.

Digital fabrication devices exploit basic technologies in order to create tangible reproductions of 3D digital models. Although current 3D printing pipelines still suffer from several restrictions, accuracy in reproduction has reached an excellent level. The manufacturing industry has been the main domain of 3D printing applications over the last decade. Digital fabrication techniques have also been demonstrated to be effective in many other contexts, including the consumer domain. The Cultural Heritage is one of the new application contexts and is an ideal domain to test the flexibility and quality of this new technology. This survey overviews the various fabrication technologies, discussing their strengths, limitations and costs. Various successful uses of 3D printing in the Cultural Heritage are analysed, which should also be useful for other application contexts. We review works that have attempted to extend fabrication technologies in order to deal with the specific issues in the use of digital fabrication in the Cultural Heritage. Finally, we also propose areas for future research.

No abstract

No abstract