Inverse global illumination: recovering reflectance models of real scenes from photographs
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
The digital Michelangelo project: 3D scanning of large statues
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
High-Quality Texture Reconstruction from Multiple Scans
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated Texture Registration and Stitching for Real World Models
PG '00 Proceedings of the 8th Pacific Conference on Computer Graphics and Applications
Acquisition and Visualization of Colored 3D Objects
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Reflectance-based Classification of Color Edges
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fusing Multiple Color Images for Texturing Models
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Cast shadow segmentation using invariant color features
Computer Vision and Image Understanding
GoLD: interactive display of huge colored and textured models
ACM SIGGRAPH 2005 Papers
ACM SIGGRAPH 2005 Papers
Mesh parameterization methods and their applications
Foundations and Trends® in Computer Graphics and Vision
Journal on Computing and Cultural Heritage (JOCCH)
3D modeling of complex and detailed cultural heritage using multi-resolution data
Journal on Computing and Cultural Heritage (JOCCH)
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Improved color acquisition and mapping on 3D models via flash-based photography
Journal on Computing and Cultural Heritage (JOCCH)
Estimating the Laplace-Beltrami operator by restricting 3D functions
SGP '09 Proceedings of the Symposium on Geometry Processing
Multiscale acquisition and presentation of very large artifacts: The case of portalada
Journal on Computing and Cultural Heritage (JOCCH)
Fast low-memory seamless photo blending on massive point clouds using a streaming framework
Journal on Computing and Cultural Heritage (JOCCH)
3D enhanced model from multiple data sources for the analysis of the cylinder seal of Ibni-Sharrum
VAST'08 Proceedings of the 9th International conference on Virtual Reality, Archaeology and Cultural Heritage
Artifacts removal for color projection on 3D models using flash light
VAST'09 Proceedings of the 10th International conference on Virtual Reality, Archaeology and Cultural Heritage
Pushing time-of-flight scanners to the limit
VAST'09 Proceedings of the 10th International conference on Virtual Reality, Archaeology and Cultural Heritage
VAST'11 Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage
Removing shadows for color projection using sun position estimation
VAST'10 Proceedings of the 11th International conference on Virtual Reality, Archaeology and Cultural Heritage
Seamless texture map generation from multiple images
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Fully Automatic Registration of Image Sets on Approximate Geometry
International Journal of Computer Vision
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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 data sets are presented.