## Archives for Technology - Page 34

Texture mapping is an essential component for creating 3D models and is widely used in both the game and the movie industries. Creating texture maps has always been a complex task and existing methods carefully balance flexibility with ease of use. One difficulty in using texturing is the repeated placement of individual textures over larger areas. In this paper, we propose a method which uses decals to place images onto a model. Our method allows the decals to compete for space and to deform as they are being pushed by other decals. A spherical field function is used to determine the position and the size of each decal and the deformation applied to fit the decals. The decals may span multiple objects with heterogeneous representations. Our method does not require an explicit parametrization of the model. As such, varieties of patterns, including repeated patterns like rocks, tiles and scales can be mapped. We have implemented the method using the GPU where placement, size and orientation of thousands of decals are manipulated in real time.
Texture mapping is an essential component for creating 3D models and is widely used in both the game and the movie industries. Creating texture maps has always been a complex task and existing methods carefully balance flexibility with ease of use. One difficulty in using texturing is the repeated placement of individual textures over larger areas. In this paper we propose a method which uses decals to place images onto a model. Our method allows the decals to compete for space and to deform as they are being pushed by other decals.

One of the most elementary application of a lattice is the quantization of real-valued s-dimensional vectors into finite bit precision to make them representable by a digital computer. Most often, the simple s-dimensional regular grid is used for this task where each component of the vector is quantized individually. However, it is known that other lattices perform better regarding the average quantization error. A rank-1 lattices is a special type of lattice, where the lattice points can be described by a single s-dimensional generator vector. Further, the number of points inside the unit cube [0, 1)s is arbitrary and can be directly enumerated by a single one-dimensional integer value. By choosing a suitable generator vector the minimum distance between the lattice points can be maximized which, as we show, leads to a nearly optimal mean quantization error. We present methods for finding parameters for s-dimensional maximized minimum distance rank-1 lattices and further show their practical use in computer graphics applications.One of the most elementary application of a lattice is the quantization of real valued s-dimensional vectors into finite bit precision to make them representable by a digital computer. Most often, the simple s-dimensional regular grid is used for this task where each component of the vector is quantized individually. However, it is known that other lattices perform better regarding the average quantization error. A rank-1 lattices is a special type of lattice, where the lattice points can be described by a single s-dimensional generator vector.

We present a method for extreme occluder simplification. We take a triangle soup as input, and produce a small set of polygons with closely matching occlusion properties. In contrast to methods that optimize the original geometry, our algorithm has very few requirements for the input— specifically, the input does not need to be a watertight, two-manifold mesh. This robustness is achieved by working on a well-behaved, discretized representation of the input instead of the original, potentially badly structured geometry. We first formulate the algorithm for individual occluders, and further introduce a hierarchy for handling large, complex scenes.We present a method for extreme occluder simplification. We take a triangle soup as input, and produce a small set of polygons with closely matching occlusion properties. In contrast to methods that optimize the original geometry, our algorithm has very few requirements for the input— specifically, the input does not need to be a watertight, two-manifold mesh. This robustness is achieved by working on a well-behaved, discretized representation of the input instead of the original, potentially badly structured geometry. We first formulate the algorithm for individual occluders, and further introduce a hierarchy for handling large, complex scenes.

We present a method for extracting complex manifolds with an arbitrary number of (self-) intersections from unoriented point clouds containing large amounts of noise. Manifolds are formed in a three-step process. First, small flat neighbourhoods of all possible orientations are created around all points. Next, neighbourhoods are assembled into larger quasi-flat patches, whose overlaps give the global connectivity structure of the point cloud. Finally, curved manifolds are extracted from the patch connectivity graph via a multiple-source flood fill. The manifolds can be reconstructed into meshed surfaces using standard existing surface reconstruction methods. We demonstrate the speed and robustness of our method on several point clouds, with applications in point cloud segmentation, denoising and medial surface reconstruction.We present a method for extracting complex manifolds with an arbitrary number of (self) intersections from unoriented point clouds containing large amounts of noise. Manifolds are formed in a three step process. First, small flat neighborhoods of all possible orientations are created around all points. Next, neighborhoods are assembled into larger quasi-flat patches, whose overlaps determine the global connectivity structure of the point cloud. Finally, curved manifolds, as well as their intersection curves, are extracted from the patch connectivity graph via a multiple-source flood fill. The extracted manifolds can be straightforwardly reconstructed into polygonal surfaces using standard surface reconstruction methods.

Interactive rigid body simulation is an important part of many modern computer tools, which no authoring tool nor game engine can do without. Such high-performance computer tools open up new possibilities for changing how designers, engineers, modelers and animators work with their design problems. This paper is a self contained state-of-the-art report on the physics, the models, the numerical methods and the algorithms used in interactive rigid body simulation all of which have evolved and matured over the past 20 years. Furthermore, the paper communicates the mathematical and theoretical details in a pedagogical manner. This paper is not only a stake in the sand on what has been done, it also seeks to give the reader deeper insights to help guide their future research.Interactive rigid body simulation is an important part of many modern computer tools, which no authoring tool nor game engine can do without. Such high performance computer tools open up new possibilities for changing how designers, engineers, modelers and animators work with their design problems. This paper is a self contained state-of-the-art report on the physics, the models, the numerical methods and the algorithms used in interactive rigid body simulation all of which have evolved and matured over the past 20 years. Furthermore, the paper communicates the mathematical and theoretical details in a pedagogical manner.

Subpixel rendering increases the apparent display resolution by taking into account the subpixel structure of a given display. In essence, each subpixel is addressed individually, allowing the underlying signal to be sampled more densely. Unfortunately, naïve subpixel sampling introduces colour aliasing, as each subpixel only displays a specific colour (usually R, G and B subpixels are used). As previous work has shown, chromatic aliasing can be reduced significantly by taking the sensitivity of the human visual system into account. In this work, we find optimal filters for subpixel rendering for a diverse set of 1D and 2D subpixel layout patterns. We demonstrate that these optimal filters can be approximated well with analytical functions. We incorporate our filters into GPU-based multi-sample anti-aliasing to yield subpixel rendering at a very low cost (1–2 ms filtering time at HD resolution). We also show that texture filtering can be adapted to perform efficient subpixel rendering. Finally, we analyse the findings of a user study we performed, which underpins the increased visual fidelity that can be achieved for diverse display layouts, by using our optimal filters.Subpixel rendering increases the apparent display resolution by taking into account the subpixel structure of a given display. In essence, each subpixel is addressed individually, allowing the underlying signal to be sampled more densely. Unfortunately, naïve subpixel sampling introduces colour aliasing, as each subpixel only displays a specific colour (usually R, G, and B subpixels are used). As previous work has shown, chromatic aliasing can be reduced significantly by taking the sensitivity of the human visual system into account. In this work, wefind optimal filters for subpixel rendering for a diverse set of 1D and 2D subpixel layout patterns.

Lagrangian coherent structures (LCSs) have become a widespread and powerful method to describe dynamic motion patterns in time-dependent flow fields. The standard way to extract LCS is to compute height ridges in the finite-time Lyapunov exponent field. In this work, we present an alternative method to approximate Lagrangian features for 2D unsteady flow fields that achieve subgrid accuracy without additional particle sampling. We obtain this by a geometric reconstruction of the flow map using additional material constraints for the available samples. In comparison to the standard method, this allows for a more accurate global approximation of LCS on sparse grids and for long integration intervals. The proposed algorithm works directly on a set of given particle trajectories and without additional flow map derivatives. We demonstrate its application for a set of computational fluid dynamic examples, as well as trajectories acquired by Lagrangian methods, and discuss its benefits and limitations.
Lagrangian Coherent Structures (LCS) have become a widespread and powerful method to describe dynamic motion patterns in time-dependent flow fields. The standard way to extract LCS is to compute height ridges in the Finite Time Lyapunov Exponent (FTLE) field. In this work, we present an alternative method to approximate Lagrangian features for 2D unsteady flow fields that achieves subgrid accuracy without additional particle sampling. We obtain this by a geometric reconstruction of the flow map using additional material constraints for the available samples. The illustration shows four approximations of LCS at different time steps in subgrid accuracy computed from a triangular grid containing 60 times 120 sample points for a heated cylinder simulation.

One of the standard techniques to visualize three-dimensional flow is to use geometry primitives. This solution, when opaque primitives are used, results in high levels of occlusion, especially with dense streamline seeding. Using semi-transparent geometry primitives can alleviate the problem of occlusion. However, with semi-transparency some parts of the data set become too vague and blurry, while others are still heavily occluded. We conducted a user study that provided us with results on perceptual limits of using semi-transparent geometry primitives for flow visualization. Texture models for semi-transparent streamlines were introduced. Test subjects were shown multiple overlaying layers of streamlines and recorded how many different flow directions they were able to perceive. The user study allowed us to identify a set of top scoring textures. We discuss the results of the user study, provide guidelines on using semi-transparency for three-dimensional flow visualization and show how varying textures for different streamlines can further enhance the perception of dense streamlines. We also discuss the strategies for dealing with very high levels of occlusion. The strategies are per-pixel filtering of flow directions, when only some of the streamlines are rendered at a particular pixel, and opacity normalization, a way of altering the opacity of overlapping streamlines with the same direction. We illustrate our results with a variety of visualizations.One of the standard techniques to visualize three-dimensional flow is to use geometry primitives. This solution, when opaque primitives are used, results in high levels of occlusion, especially with dense streamline seeding. Using semi-transparent geometry primitives can alleviate the problem of occlusion. However, with semi-transparency some parts of the data set become too vague and blurry, while others are still heavily occluded. We conducted a user study that provided us with results on perceptual limits of using semi-transparent geometry primitives for flow visualization. Texture models for semi-transparent streamlines were introduced. Test subjects were shown multiple overlaying layers of streamlines and recorded how many different flow directions they were able to perceive. The user study allowed us to identify a set of top scoring textures. We discuss the results of the user study, provide guidelines on using semi-transparency for three-dimensional flow visualization and show how varying textures for different streamlines can further enhance the perception of dense streamlines. We also discuss the strategies for dealing with very high levels of occlusion. The strategies are per-pixel filtering of flow directions, when only some of the streamlines are rendered at a particular pixel, and opacity normalization, a way of altering the opacity of overlapping streamlines with the same direction. We illustrate our results with a variety of visualizations.

This paper presents a procedure for modelling aggregates such as piles that consist of arbitrary components. The method generates an aggregate of components that need to be accumulated, and an aggregate shape represents the surface of the target aggregate. The number of components and their positions and orientations are controlled by five parameters. The components, the aggregate shape and the parameters are the inputs for the method which involves placement and refinement steps. In the placement step, the orientation and initial position of a component are determined by a non-periodic placement such that each component overlaps its neighbours. In the refinement step, to construct a pile structure, the position of each component is adjusted by reducing the overlap.This paper presents a procedure for modelling aggregates such as piles that consist of arbitrary components. The method generates an aggregate of components that need to be accumulated, and an aggregate shape represents the surface of the target aggregate. The number of components and their positions and orientations are controlled by five parameters. The components, the aggregate shape and the parameters are the inputs for the method which involves placement and refinement steps. In the placement step, the orientation and initial position of a component are determined by a non-periodic placement such that each component overlaps its neighbours. In the refinement step, to construct a pile structure, the position of each component is adjusted by reducing the overlap.

The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three-dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real-time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy.The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three-dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real-time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy.