35-Issue 2

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/15061

Browse

Now showing 1 - 7 of 7

Boundary Detection in Particle-based Fluids
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Sandim, Marcos; Cedrim, Douglas; Nonato, Luis Gustavo; Pagliosa, Paulo; Paiva, Afonso; Joaquim Jorge and Ming Lin
This paper presents a novel method to detect free-surfaces on particle-based volume representation. In contrast to most particlebased free-surface detection methods, which perform the surface identification based on physical and geometrical properties derived from the underlying fluid flow simulation, the proposed approach only demands the spatial location of the particles to properly recognize surface particles, avoiding even the use of kernels. Boundary particles are identified through a Hidden Point Removal (HPR) operator used for visibility test. Our method is very simple, fast, easy to implement and robust to changes in the distribution of particles, even when facing large deformation of the free-surface. A set of comparisons against state-of-the-art boundary detection methods show the effectiveness of our approach. The good performance of our method is also attested in the context of fluid flow simulation involving free-surface, mainly when using level-sets for rendering purposes.
Building Construction Sets by Tiling Grammar Simplification
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Kalojanov, Javor; Wand, Michael; Slusallek, Philipp; Joaquim Jorge and Ming Lin
This paper poses the problem of fabricating physical construction sets from example geometry: A construction set provides a small number of different types of building blocks from which the example model as well as many similar variants can be reassembled. This process is formalized by tiling grammars. Our core contribution is an approach for simplifying tiling grammars such that we obtain physically manufacturable building blocks of controllable granularity while retaining variability, i.e., the ability to construct many different, related shapes. Simplification is performed by sequences of two types of elementary operations: non-local joint edge collapses in the tile graphs reduce the granularity of the decomposition and approximate replacement operations reduce redundancy. We evaluate our method on abstract graph grammars in addition to computing several physical construction sets, which are manufactured using a commodity 3D printer.
Buoyancy Optimization for Computational Fabrication
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Wang, Lingfeng; Whiting, Emily; Joaquim Jorge and Ming Lin
This paper introduces a design and fabrication pipeline for creating floating forms. Our method optimizes for buoyant equilibrium and stability of complex 3D shapes, applying a voxel-carving technique to control the mass distribution. The resulting objects achieve a desired floating pose defined by a user-specified waterline height and orientation. In order to enlarge the feasible design space, we explore novel ways to load the interior of a design using prefabricated components and casting techniques. 3D printing is employed for high-precision fabrication. For larger scale designs we introduce a method for stacking lasercut planar pieces to create 3D objects in a quick and economic manner. We demonstrate fabricated designs of complex shape in a variety of floating poses.
Effect of Low-level Visual Details in Perception of Deformation
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Han, Donghui; Keyser, John; Joaquim Jorge and Ming Lin
We quantitatively measure how different low-level visual details can influence people's perceived stiffness of a deformable sphere under physically based simulation. The result can be used to create a metric for artists in designing textures to enhance or reduce the stiffness perceived by a viewer. We use a checkerboard texture to render the simulation of a free falling sphere that collides with the ground and bounces up. We vary the spatial frequency and contrast of the checkerboard pattern according to results seen in a previous study on the Spatial- Temporal Contrast Sensitivity Function (CSF).We find that checkerboard pattern with certain combinations of spatial frequency and contrast can reduce the perceived stiffness. We also add a high contrast checkerboard background to study how complex backgrounds can influence the effect of low-level details in textures of foreground objects. Our study shows that the effect of low-level visual details in foreground objects observed previously disappears in this situation. This indicates the importance of background, even if it is static.
Geometric Flows of Curves in Shape Space for Processing Motion of Deformable Objects
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Brandt, Christopher; Tycowicz, Christoph von; Hildebrandt, Klaus; Joaquim Jorge and Ming Lin
We introduce techniques for the processing of motion and animations of non-rigid shapes. The idea is to regard animations of deformable objects as curves in shape space. Then, we use the geometric structure on shape space to transfer concepts from curve processing in Rn to the processing of motion of non-rigid shapes. Following this principle, we introduce a discrete geometric flow for curves in shape space. The flow iteratively replaces every shape with a weighted average shape of a local neighborhood and thereby globally decreases an energy whose minimizers are discrete geodesics in shape space. Based on the flow, we devise a novel smoothing filter for motions and animations of deformable shapes. By shortening the length in shape space of an animation, it systematically regularizes the deformations between consecutive frames of the animation. The scheme can be used for smoothing and noise removal, e.g., for reducing jittering artifacts in motion capture data. We introduce a reduced-order method for the computation of the flow. In addition to being efficient for the smoothing of curves, it is a novel scheme for computing geodesics in shape space. We use the scheme to construct non-linear ''Bézier curves'' by executing de Casteljau's algorithm in shape space.
Learning 3D Deformation of Animals from 2D Images
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Kanazawa, Angjoo; Kovalsky, Shahar; Basri, Ronen; Jacobs, David; Joaquim Jorge and Ming Lin
Understanding how an animal can deform and articulate is essential for a realistic modification of its 3D model. In this paper, we show that such information can be learned from user-clicked 2D images and a template 3D model of the target animal. We present a volumetric deformation framework that produces a set of new 3D models by deforming a template 3D model according to a set of user-clicked images. Our framework is based on a novel locally-bounded deformation energy, where every local region has its own stiffness value that bounds how much distortion is allowed at that location. We jointly learn the local stiffness bounds as we deform the template 3D mesh to match each user-clicked image. We show that this seemingly complex task can be solved as a sequence of convex optimization problems. We demonstrate the effectiveness of our approach on cats and horses, which are highly deformable and articulated animals. Our framework produces new 3D models of animals that are significantly more plausible than methods without learned stiffness.
Space-Time Co-Segmentation of Articulated Point Cloud Sequences
(The Eurographics Association and John Wiley & Sons Ltd., 2016) Yuan, Qing; Li, Guiqing; Xu, Kai; Chen, Xudong; Huang, Hui; Joaquim Jorge and Ming Lin
Consistent segmentation is to the center of many applications based on dynamic geometric data. Directly segmenting a raw 3D point cloud sequence is a challenging task due to the low data quality and large inter-frame variation across the whole sequence. We propose a local-to-global approach to co-segment point cloud sequences of articulated objects into near-rigid moving parts. Our method starts from a per-frame point clustering, derived from a robust voting-based trajectory analysis. The local segments are then progressively propagated to the neighboring frames with a cut propagation operation, and further merged through all frames using a novel space-time segment grouping technqiue, leading to a globally consistent and compact segmentation of the entire articulated point cloud sequence. Such progressive propagating and merging, in both space and time dimensions, makes our co-segmentation algorithm especially robust in handling noise, occlusions and pose/view variations that are usually associated with raw scan data.

Browse

Browsing 35-Issue 2 by Subject "Computational Geometry and Object Modeling"

Results Per Page

Sort Options