2,527 research outputs found
ITEM: Inter-Texture Error Measurement for 3D Meshes
We introduce a simple and innovative method to compare any two texture maps, regardless of their sizes, aspect ratios, or even masks, as long as they are both meant to be mapped onto the same 3D mesh. Our system is based on a zero-distortion 3D mesh unwrapping technique which compares two new adapted texture atlases with the same mask but different texel colors, and whose every texel covers the same area in 3D. Once these adapted atlases are created, we measure their difference with ITEM-RMSE, a slightly modified version of the standard RMSE defined for images. ITEM-RMSE is more meaningful and reliable than RMSE because it only takes into account the texels inside the mask, since they are the only ones that will actually be used during rendering. Our method is not only very useful to compare the space efficiency of different texture atlas generation algorithms, but also to quantify texture loss in compression schemes for multi-resolution textured 3D meshes
Beyond developable: computational design and fabrication with auxetic materials
We present a computational method for interactive 3D design and rationalization of surfaces via auxetic materials, i.e., flat flexible material that can stretch uniformly up to a certain extent. A key motivation for studying such material is that one can approximate doubly-curved surfaces (such as the sphere) using only flat pieces, making it attractive for fabrication. We physically realize surfaces by introducing cuts into approximately inextensible material such as sheet metal, plastic, or leather. The cutting pattern is modeled as a regular triangular linkage that yields hexagonal openings of spatially-varying radius when stretched. In the same way that isometry is fundamental to modeling developable surfaces, we leverage conformal geometry to understand auxetic design. In particular, we compute a global conformal map with bounded scale factor to initialize an otherwise intractable non-linear optimization. We demonstrate that this global approach can handle non-trivial topology and non-local dependencies inherent in auxetic material. Design studies and physical prototypes are used to illustrate a wide range of possible applications
3D Mesh Simplification. A survey of algorithms and CAD model simplification tests
Simplification of highly detailed CAD models is an important step when CAD
models are visualized or by other means utilized in augmented reality applications.
Without simplification, CAD models may cause severe processing and storage is-
sues especially in mobile devices. In addition, simplified models may have other
advantages like better visual clarity or improved reliability when used for visual pose
tracking. The geometry of CAD models is invariably presented in form of a 3D
mesh. In this paper, we survey mesh simplification algorithms in general and focus
especially to algorithms that can be used to simplify CAD models. We test some
commonly known algorithms with real world CAD data and characterize some new
CAD related simplification algorithms that have not been surveyed in previous mesh
simplification reviews.Siirretty Doriast
A Decoupled 3D Facial Shape Model by Adversarial Training
Data-driven generative 3D face models are used to compactly encode facial
shape data into meaningful parametric representations. A desirable property of
these models is their ability to effectively decouple natural sources of
variation, in particular identity and expression. While factorized
representations have been proposed for that purpose, they are still limited in
the variability they can capture and may present modeling artifacts when
applied to tasks such as expression transfer. In this work, we explore a new
direction with Generative Adversarial Networks and show that they contribute to
better face modeling performances, especially in decoupling natural factors,
while also achieving more diverse samples. To train the model we introduce a
novel architecture that combines a 3D generator with a 2D discriminator that
leverages conventional CNNs, where the two components are bridged by a geometry
mapping layer. We further present a training scheme, based on auxiliary
classifiers, to explicitly disentangle identity and expression attributes.
Through quantitative and qualitative results on standard face datasets, we
illustrate the benefits of our model and demonstrate that it outperforms
competing state of the art methods in terms of decoupling and diversity.Comment: camera-ready version for ICCV'1
Optimal Point Placement for Mesh Smoothing
We study the problem of moving a vertex in an unstructured mesh of
triangular, quadrilateral, or tetrahedral elements to optimize the shapes of
adjacent elements. We show that many such problems can be solved in linear time
using generalized linear programming. We also give efficient algorithms for
some mesh smoothing problems that do not fit into the generalized linear
programming paradigm.Comment: 12 pages, 3 figures. A preliminary version of this paper was
presented at the 8th ACM/SIAM Symp. on Discrete Algorithms (SODA '97). This
is the final version, and will appear in a special issue of J. Algorithms for
papers from SODA '9
RTIN-based strategies for local mesh refinement
summary:Longest-edge bisection algorithms are often used for local mesh refinements within the finite element method in 2D. In this paper, we discuss and describe their conforming variant. A particular attention is devoted to the so-called Right-Triangulated Irregular Network (RTIN) based on isosceles right triangles and its tranformation to more general domains. We suggest to combine RTIN with a balanced quadrant tree (QuadTree) decomposition. This combination does not produce hanging nodes within the mesh refinements and could be extended to tetrahedral meshes in 3D
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