Browsing 38-Issue 5 by Title
Now showing items 10-16 of 16
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On Evaluating Consensus in RANSAC Surface Registration
(The Eurographics Association and John Wiley & Sons Ltd., 2019)Random Sample Consensus is a powerful paradigm that was successfully applied in various contexts, including Location Determination Problem, fundamental matrix estimation and global 3D surface registration, where many ... -
Parallel Globally Consistent Normal Orientation of Raw Unorganized Point Clouds
(The Eurographics Association and John Wiley & Sons Ltd., 2019)A mandatory component for many point set algorithms is the availability of consistently oriented vertex-normals (e.g. for surface reconstruction, feature detection, visualization). Previous orientation methods on meshes ... -
Point Pattern Synthesis via Irregular Convolution
(The Eurographics Association and John Wiley & Sons Ltd., 2019)Point pattern synthesis is a fundamental tool with various applications in computer graphics. To synthesize a point pattern, some techniques have taken an example-based approach, where the user provides a small exemplar ... -
Structural Design Using Laplacian Shells
(The Eurographics Association and John Wiley & Sons Ltd., 2019)We introduce a method to design lightweight shell objects that are structurally robust under the external forces they may experience during use. Given an input 3D model and a general description of the external forces, our ... -
Structured Regularization of Functional Map Computations
(The Eurographics Association and John Wiley & Sons Ltd., 2019)We consider the problem of non-rigid shape matching using the functional map framework. Specifically, we analyze a commonly used approach for regularizing functional maps, which consists in penalizing the failure of the ... -
Symposium on Geometry Processing 2019 - CGF38-5: Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2019) -
Unsupervised Cycle-consistent Deformation for Shape Matching
(The Eurographics Association and John Wiley & Sons Ltd., 2019)We propose a self-supervised approach to deep surface deformation. Given a pair of shapes, our algorithm directly predicts a parametric transformation from one shape to the other respecting correspondences. Our insight is ...