Zobrazeno 1 - 10
of 254
pro vyhledávání: '"Pajarola Renato"'
Autor:
Zawallich, Lars, Pajarola, Renato
When folding a 3D object from a 2D material like paper, typically only an approximation of the original surface geometry is needed. Such an approximation can effectively be created by a (progressive) mesh simplification approach, e.g. using an edge c
Externí odkaz:
http://arxiv.org/abs/2405.07922
Autor:
Erler, Philipp, Fuentes, Lizeth, Hermosilla, Pedro, Guerrero, Paul, Pajarola, Renato, Wimmer, Michael
Publikováno v:
Computer Graphics Forum e15000, 2024
3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage, and engineering. Current approaches either try to optimize a non-data-driven surface representation to fit the points
Externí odkaz:
http://arxiv.org/abs/2401.08518
Recent years have seen a proliferation of new digital products for the efficient management of indoor spaces, with important applications like emergency management, virtual property showcasing and interior design. These products rely on accurate 3D m
Externí odkaz:
http://arxiv.org/abs/2103.00262
Publikováno v:
Computer Graphics Forum 39 (2020) 443-453
Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limi
Externí odkaz:
http://arxiv.org/abs/1909.05511
Autor:
Perez, Lizeth J. Fuentes, Calla, Luciano A. Romero, Montenegro, Anselmo A., Mura, Claudio, Pajarola, Renato
The sparse representation of signals defined on Euclidean domains has been successfully applied in signal processing. Bringing the power of sparse representations to non-regular domains is still a challenge, but promising approaches have started emer
Externí odkaz:
http://arxiv.org/abs/1810.08266
Insightful visualization of multidimensional scalar fields, in particular parameter spaces, is key to many fields in computational science and engineering. We propose a principal component-based approach to visualize such fields that accurately refle
Externí odkaz:
http://arxiv.org/abs/1809.03618
Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy compression al
Externí odkaz:
http://arxiv.org/abs/1806.05952
Developing complex, real world graphics applications which leverage multiple GPUs and computers for interactive 3D rendering tasks is a complex task. It requires expertise in distributed systems and parallel rendering in addition to the application d
Externí odkaz:
http://arxiv.org/abs/1802.08022
Following up on the success of the analysis of variance (ANOVA) decomposition and the Sobol indices (SI) for global sensitivity analysis, various related quantities of interest have been defined in the literature including the effective and mean dime
Externí odkaz:
http://arxiv.org/abs/1712.01633
Sobol indices are a widespread quantitative measure for variance-based global sensitivity analysis, but computing and utilizing them remains challenging for high-dimensional systems. We propose the tensor train decomposition (TT) as a unified framewo
Externí odkaz:
http://arxiv.org/abs/1712.00233