Topographic Map Visualization from Adaptively Compressed Textures

Raster‐based topographic maps are commonly used in geoinformation systems to overlay geographic entities on top of digital terrain models. Using compressed texture formats for encoding topographic maps allows reducing latency times while visualizing large geographic datasets. Topographic maps encompass high‐frequency content with large uniform regions, making current compressed texture formats inappropriate for encoding them. In this paper we present a method for locally‐adaptive compression of topographic maps. Key elements include a Hilbert scan to maximize spatial coherence, efficient encoding of homogeneous image regions through arbitrarily‐sized texel runs, a cumulative run‐length encoding supporting fast random‐access, and a compression algorithm supporting lossless and lossy compression. Our scheme can be easily implemented on current programmable graphics hardware allowing real‐time GPU decompression and rendering of bilinear‐filtered topographic maps.     

A Practical Method for High‐Resolution Embedded Liquid Surfaces

Combining high‐resolution level set surface tracking with lower resolution physics is an inexpensive method for achieving highly detailed liquid animations. Unfortunately, the inherent resolution mismatch introduces several types of disturbing visual artifacts. We identify the primary sources of these artifacts and present simple, efficient, and practical solutions to address them. First, we propose an unconditionally stable filtering method that selectively removes sub‐grid surface artifacts not seen by the fluid physics, while preserving fine detail in dynamic splashing regions. It provides comparable results to recent error‐correction techniques at lower cost, without substepping, and with better scaling behavior. Second, we show how a modified narrow‐band scheme can ensure accurate free surface boundary conditions in the presence of large resolution mismatches. Our scheme preserves the efficiency of the narrow‐band methodology, while eliminating objectionable stairstep artifacts observed in prior work. Third, we demonstrate that the use of linear interpolation of velocity during advection of the high‐resolution level set surface is responsible for visible grid‐aligned kinks; we therefore advocate higher‐order velocity interpolation, and show that it dramatically reduces this artifact. While these three contributions are orthogonal, our results demonstrate that taken together they efficiently address the dominant sources of visual artifacts arising with high‐resolution embedded liquid surfaces; the proposed approach offers improved visual quality, a straightforward implementation, and substantially greater scalability than competing methods.     

Adaptive Compression of Texture Pyramids

High‐quality texture minification techniques, including trilinear and anisotropic filtering, require texture data to be arranged into a collection of pre‐filtered texture maps called mipmaps. In this paper, we present a compression scheme for mipmapped textures which achieves much higher quality than current native schemes by exploiting image coherence across mipmap levels. The basic idea is to use a high‐quality native compressed format for the upper levels of the mipmap pyramid (to retain efficient minification filtering) together with a novel compact representation of the detail provided by the highest‐resolution mipmap. Key elements of our approach include delta‐encoding of the luminance signal, efficient encoding of coherent regions through texel runs following a Hilbert scan, a scheme for run encoding supporting fast random‐access, and a predictive approach for encoding indices of variable‐length blocks. We show that our scheme clearly outperforms native 6:1 compressed texture formats in terms of image quality while still providing real‐time rendering of trilinearly filtered textures.     

Animated 3D Line Drawings with Temporal Coherence

Producing traditional animation is a laborious task where the key drawings are first drawn by artists and thereafter inbetween drawings are created, whether it is by hand or computer‐assisted. Auto‐inbetweening of these 2D key drawings by computer is a non‐trivial task as 3D depths are missing. An alternate approach is to generate all the drawings by extracting lines directly from animated 3D models frame by frame, concatenating and rendering them together into an animation. However, animation quality generated using this straightforward method bears two problems. Firstly, the animation contains unsatisfactory visual artifacts such as line flickering and popping. This is especially pronounced when the lines are extracted using high‐order derivatives, such as ridges and valleys, from 3D models represented in triangle meshes. Secondly, there is a lack of temporal continuity as each drawing is generated without taking its neighboring drawings into consideration. In this paper, we propose an improved approach over the straightforward method by transferring extracted 3D line drawings of each frame into individual 3D lines and processing them along the time domain. Our objective is to minimize the visual artifacts and incorporate temporal relationship of individual lines throughout the entire animation sequence. This is achieved by creating correspondent trajectory of each line from each frame and applying global optimization on each trajectory. To realize this target, we present a fully automatic novel approach, which consists of (1) a line matching algorithm, (2) an optimizing algorithm, taking into account both the variations of numbers and lengths of 3D lines in each frame, and (3) a robust tracing method for transferring collections of line segments extracted from the 3D models into individual lines. We evaluate our approach on several animated model sequences to demonstrate its effectiveness in producing line drawing animations with temporal coherence.     

Real‐Time Concurrent Linked List Construction on the GPU

We introduce a method to dynamically construct highly concurrent linked lists on modern graphics processors. Once constructed, these data structures can be used to implement a host of algorithms useful in creating complex rendering effects in real time. We present a straightforward way to create these linked lists using generic atomic operations available in APIs such as OpenGL 4.0 and DirectX 11. We also describe several possible applications of our algorithm. One example uses per‐pixel linked lists for order‐independent transparency; as a consequence, we are able to directly implement fully programmable blending, which frees developers from the restrictions imposed by current graphics APIs. The second uses linked lists to implement real‐time indirect shadows.     

Temporally Coherent Adaptive Sampling for Imperfect Shadow Maps

We propose a new adaptive algorithm for determining virtual point lights (VPL) in the scope of real‐time instant radiosity methods, which use a limited number of VPLs. The proposed method is based on Metropolis‐Hastings sampling and exhibits better temporal coherence of VPLs, which is particularly important for real‐time applications dealing with dynamic scenes. We evaluate the properties of the proposed method in the context of the algorithm based on imperfect shadow maps and compare it with the commonly used inverse transform method. The results indicate that the proposed technique can significantly reduce the temporal flickering artifacts even for scenes with complex materials and textures. Further, we propose a novel splatting scheme for imperfect shadow maps using hardware tessellation. This scheme significantly improves the rendering performance particularly for complex and deformable scenes. We thoroughly analyze the performance of the proposed techniques on test scenes with detailed materials, moving camera, and deforming geometry.     

Memory-Conserving Bounding Volume Hierarchies with Coherent Raytracing

Bounding volume hierarchies (BVHs) are a popular method for speeding up raytracing, but they can consume a large amount of memory for complex scenes. We investigate a hierarchical scheme for encoding BVHs that reduces the BVH storage requirements by 63%–75%. The computational overhead of the scheme can be reduced to negligible levels by shooting bundles of rays through the BVH (coherent raytracing). This gives the speed of a coherency‐based raytracer combined with substantial memory savings.     

Lazy Visibility Evaluation for Exact Soft Shadows

This paper presents a novel approach to compute high quality and noise‐free soft shadows using exact visibility computations. This work relies on a theoretical framework allowing to group lines according to the geometry they intersect. From this study, we derive a new algorithm encoding lazily the visibility from a polygon. Contrary to previous works on from‐polygon visibility, our approach is very robust and straightforward to implement. We apply this algorithm to solve exactly and efficiently the visibility of an area light source from any point in a scene. As a consequence, results are not sensitive to noise, contrary to soft shadows methods based on area light source sampling. We demonstrate the reliability of our approach on different scenes and configurations.     

Texture Compression using Wavelet Decomposition

In this paper we introduce a new fixed‐rate texture compression scheme based on the energy compaction properties of a modified Haar transform. The coefficients of this transform are quantized and stored using standard block compression methods, such as DXTC and BC7, ensuring simple implementation and very fast decoding speeds. Furthermore, coefficients with the highest contribution to the final image are quantized with higher accuracy, improving the overall compression quality. The proposed modifications to the standard Haar transform, along with a number of additional optimizations, improve the coefficient quantization and reduce the compression error. The resulting method offers more flexibility than the currently available texture compression formats, providing a variety of additional low bitrate encoding modes for the compression of grayscale and color textures.     

Caustic Forecasting: Unbiased Estimation of Caustic Lighting for Global Illumination

We present an unbiased method for generating caustic lighting using importance sampled Path Tracing with Caustic Forecasting. Our technique is part of a straightforward rendering scheme which extends the Illumination by Weak Singularities method to allow for fully unbiased global illumination with rapid convergence. A photon shooting preprocess, similar to that used in Photon Mapping, generates photons that interact with specular geometry. These photons are then clustered, effectively dividing the scene into regions which will contribute similar amounts of caustic lighting to the image. Finally, the photons are stored into spatial data structures associated with each cluster, and the clusters themselves are organized into a spatial data structure for fast searching. During rendering we use clusters to decide the caustic energy importance of a region, and use the local photons to aid in importance sampling, effectively reducing the number of samples required to capture caustic lighting.     

A Colour Interpolation Scheme for Topologically Unrestricted Gradient Meshes

Gradient meshes are a 2D vector graphics primitive where colour is interpolated between mesh vertices. The current implementations of gradient meshes are restricted to rectangular mesh topology. Our new interpolation method relaxes this restriction by supporting arbitrary manifold topology of the input gradient mesh. Our method is based on the Catmull‐Clark subdivision scheme, which is well‐known to support arbitrary mesh topology in 3D. We adapt this scheme to support gradient mesh colour interpolation, adding extensions to handle interpolation of colours of the control points, interpolation only inside the given colour space and emulation of gradient constraints seen in related closed‐form solutions. These extensions make subdivision a viable option for interpolating arbitrary‐topology gradient meshes for 2D vector graphics.     

Data‐Parallel Decompression of Triangle Mesh Topology

We propose a lossless, single‐rate triangle mesh topology codec tailored for fast data‐parallel GPU decompression. Our compression scheme coherently orders generalized triangle strips in memory. To unpack generalized triangle strips efficiently, we propose a novel parallel and scalable algorithm. We order vertices coherently to further improve our compression scheme. We use a variable bit‐length code for additional compression benefits, for which we propose a scalable data‐parallel decompression algorithm. For a set of standard benchmark models, we obtain (min: 3.7, med: 4.6, max: 7.6) bits per triangle. Our CUDA decompression requires only about 15% of the time it takes to render the model even with a simple shader.     

Computing Local Signed Distance Fields for Large Polygonal Models

The signed distance field for a polygonal model is a useful representation that facilitates efficient computation in many visualization and geometric processing tasks. Often it is more effective to build a local distance field only within a narrow band around the surface that holds local geometric information for the model. In this paper, we present a novel technique to construct a volumetric local signed distance field of a polygonal model. To compute the local field efficiently, exactly those cells that cross the polygonal surface are found first through a new voxelization method, building a list of intersecting triangles for each boundary cell. After their neighboring cells are classified, the triangle lists are exploited to compute the local signed distance field with minimized voxel‐to‐triangle distance computations. While several efficient methods for computing the distance field, particularly those harnessing the graphics processing unit's (GPU's) processing power, have recently been proposed, we focus on a CPU‐based technique, intended to deal flexibly with large polygonal models and high‐resolution grids that are often too bulky for GPU computation.     

An explicit structure‐preserving numerical scheme for EPDiff

We present a new structure‐preserving numerical scheme for solving the Euler‐Poincaré Differential (EPDiff) equation on arbitrary triangle meshes. Unlike existing techniques, our method solves the difficult non‐linear EPDiff equation by constructing energy preserving, yet fully explicit, update rules. Our approach uses standard differential operators on triangle meshes, allowing for a simple and efficient implementation. Key to the structure‐preserving features that our method exhibits is a novel numerical splitting scheme. Namely, we break the integration into three steps which rely on linear solves with a fixed sparse matrix that is independent of the simulation and thus can be pre‐factored. We test our method in the context of simulating concentrated reconnecting wavefronts on flat and curved domains. In particular, EPDiff is known to generate geometrical fronts which exhibit wave‐like behavior when they interact with each other. In addition, we also show that at a small additional cost, we can produce globally‐supported periodic waves by using our simulated fronts with wavefronts tracking techniques. We provide quantitative graphs showing that our method exactly preserves the energy in practice. In addition, we demonstrate various interesting results including annihilation and recreation of a circular front, a wave splitting and merging when hitting an obstacle and two separate fronts propagating and bending due to the curvature of the domain.     

Data‐Driven Crowd Motion Control With Multi‐Touch Gestures

Controlling a crowd using multi‐touch devices appeals to the computer games and animation industries, as such devices provide a high‐dimensional control signal that can effectively define the crowd formation and movement. However, existing works relying on pre‐defined control schemes require the users to learn a scheme that may not be intuitive. We propose a data‐driven gesture‐based crowd control system, in which the control scheme is learned from example gestures provided by different users. In particular, we build a database with pairwise samples of gestures and crowd motions. To effectively generalize the gesture style of different users, such as the use of different numbers of fingers, we propose a set of gesture features for representing a set of hand gesture trajectories. Similarly, to represent crowd motion trajectories of different numbers of characters over time, we propose a set of crowd motion features that are extracted from a Gaussian mixture model. Given a run‐time gesture, our system extracts the K nearest gestures from the database and interpolates the corresponding crowd motions in order to generate the run‐time control. Our system is accurate and efficient, making it suitable for real‐time applications such as real‐time strategy games and interactive animation controls.     

Non‐iterative Second‐order Approximation of Signed Distance Functions for Any Isosurface Representation

Signed distance functions (SDF) to explicit or implicit surface representations are intensively used in various computer graphics and visualization algorithms. Among others, they are applied to optimize collision detection, are used to reconstruct data fields or surfaces, and, in particular, are an obligatory ingredient for most level set methods. Level set methods are common in scientific visualization to extract surfaces from scalar or vector fields. Usual approaches for the construction of an SDF to a surface are either based on iterative solutions of a special partial differential equation or on marching algorithms involving a polygonization of the surface. We propose a novel method for a non‐iterative approximation of an SDF and its derivatives in a vicinity of a manifold. We use a second‐order algebraic fitting scheme to ensure high accuracy of the approximation. The manifold is defined (explicitly or implicitly) as an isosurface of a given volumetric scalar field. The field may be given at a set of irregular and unstructured samples. Stability and reliability of the SDF generation is achieved by a proper scaling of weights for the Moving Least Squares approximation, accurate choice of neighbors, and appropriate handling of degenerate cases. We obtain the solution in an explicit form, such that no iterative solving is necessary, which makes our approach fast.     

T‐SAH: Animation Optimized Bounding Volume Hierarchies

We propose a method for creating a bounding volume hierarchy (BVH) that is optimized for all frames of a given animated scene. The method is based on a novel extension of surface area heuristic to temporal domain (T‐SAH). We perform iterative BVH optimization using T‐SAH and create a single BVH accounting for scene geometry distribution at different frames of the animation. Having a single optimized BVH for the whole animation makes our method extremely easy to integrate to any application using BVHs, limiting the per‐frame overhead only to refitting the bounding volumes. We evaluated the T‐SAH optimized BVHs in the scope of real‐time GPU ray tracing. We demonstrate, that our method can handle even highly complex inputs with large deformations and significant topology changes. The results show, that in a vast majority of tested scenes our method provides significantly better run‐time performance than traditional SAH and also better performance than GPU based per‐frame BVH rebuild.     

Geometry and Attribute Compression for Voxel Scenes

Voxel‐based approaches are today's standard to encode volume data. Recently, directed acyclic graphs (DAGs) were successfully used for compressing sparse voxel scenes as well, but they are restricted to a single bit of (geometry) information per voxel. We present a method to compress arbitrary data, such as colors, normals, or reflectance information. By decoupling geometry and voxel data via a novel mapping scheme, we are able to apply the DAG principle to encode the topology, while using a palette‐based compression for the voxel attributes, leading to a drastic memory reduction. Our method outperforms existing state‐of‐the‐art techniques and is well‐suited for GPU architectures. We achieve real‐time performance on commodity hardware for colored scenes with up to 17 hierarchical levels (a 128K³voxel resolution), which are stored fully in core.     

A phenomenological model for throughfall rendering in real‐time

This paper aims at rendering interactive visual effects inherent to complex interactions between trees and rain in real‐time in order to increase the realism of natural rainy scenes. Such a complex phenomenon involves a great number of physical processes influenced by various interlinked factors and its rendering represents a thorough challenge in Computer Graphics. We approach this problem by introducing an original method to render drops dripping from leaves after interception of raindrops by foliage. Our method introduces a new hydrological model representing interactions between rain and foliage through a phenomenological approach. Our model reduces the complexity of the phenomenon by representing multiple dripping drops with a new fully functional form evaluated per‐pixel on‐the‐fly and providing improved control over density and physical properties. Furthermore, an efficient real‐time rendering scheme, taking full advantage of latest GPU hardware capabilities, allows the rendering of a large number of dripping drops even for complex scenes.     

An Adaptive Contact Model for the Robust Simulation of Knots

In this paper, we present an adaptive model for dynamically deforming hyper‐elastic rods. In contrast to existing approaches, adaptively introduced control points are not governed by geometric subdivision rules. Instead, their states are determined by employing a non‐linear energy‐minimization approach. Since valid control points are computed instantaneously, post‐stabilization schemes are avoided and the stability of the dynamic simulation is improved. Due to inherently complex contact configurations, the simulation of knot tying using rods is a challenging task. In order to address this problem, we combine our adaptive model with a robust and accurate collision handling method for elastic rods. By employing our scheme, complex knot configurations can be simulated in a physically plausible way.