Fast Extraction of High‐quality Crease Surfaces for Visual Analysis

We present a novel algorithm for the efficient extraction and visualization of high‐quality ridge and valley surfaces from numerical datasets. Despite their rapidly increasing popularity in visualization, these so‐called crease surfaces remain challenging to compute owing to their strongly nonlinear and non‐orientable nature, and their complex boundaries. In this context, existing meshing techniques require an extremely dense sampling that is computationally prohibitive. Our proposed solution intertwines sampling and meshing steps to yield an accurate approximation of the underlying surfaces while ensuring the geometric quality of the resulting mesh. Using the computation power of the GPU, we propose a fast, parallel method for sampling. Additionally, we present a new front propagation meshing strategy that leverages CPU multiprocessing. Results are shown for synthetic, medical and fluid dynamics datasets.     

Goal‐based Caustics

We propose a novel system for designing and manufacturing surfaces that produce desired caustic images when illuminated by a light source. Our system is based on a nonnegative image decomposition using a set of possibly overlapping anisotropic Gaussian kernels. We utilize this decomposition to construct an array of continuous surface patches, each of which focuses light onto one of the Gaussian kernels, either through refraction or reflection. We show how to derive the shape of each continuous patch and arrange them by performing a discrete assignment of patches to kernels in the desired caustic. Our decomposition provides for high fidelity reconstruction of natural images using a small collection of patches. We demonstrate our approach on a wide variety of caustic images by manufacturing physical surfaces with a small number of patches.     

Pathway Preserving Representation of Metabolic Networks

Improvements in biological data acquisition and genomes sequencing now allow to reconstruct entire metabolic networks of many living organisms. The size and complexity of these networks prohibit manual drawing and thereby urge the need of dedicated visualization techniques. An efficient representation of such a network should preserve the topological information of metabolic pathways while respecting biological drawing conventions. These constraints complicate the automatic generation of such visualization as it raises graph drawing issues. In this paper we propose a method to lay out the entire metabolic network while preserving the pathway information as much as possible. That method is flexible as it enables the user to define whether or not node duplication should be performed, to preserve or not the network topology. Our technique combines partitioning, node placement and edge bundling to provide a pseudo‐orthogonal visualization of the metabolic network. To ease pathway information retrieval, we also provide complementary interaction tools that emphasize relevant pathways in the entire metabolic context.     

Uncertainty‐Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction

Systems projecting a continuous n‐dimensional parameter space to a continuous m‐dimensional target space play an important role in science and engineering. If evaluating the system is expensive, however, an analysis is often limited to a small number of sample points. The main contribution of this paper is an interactive approach to enable a continuous analysis of a sampled parameter space with respect to multiple target values. We employ methods from statistical learning to predict results in real‐time at any user‐defined point and its neighborhood. In particular, we describe techniques to guide the user to potentially interesting parameter regions, and we visualize the inherent uncertainty of predictions in 2D scatterplots and parallel coordinates. An evaluation describes a real‐world scenario in the application context of car engine design and reports feedback of domain experts. The results indicate that our approach is suitable to accelerate a local sensitivity analysis of multiple target dimensions, and to determine a sufficient local sampling density for interesting parameter regions.     

Curve Density Estimates

In this work, we present a technique based on kernel density estimation for rendering smooth curves. With this approach, we produce uncluttered and expressive pictures, revealing frequency information about one, or, multiple curves, independent of the level of detail in the data, the zoom level, and the screen resolution. With this technique the visual representation scales seamlessly from an exact line drawing, (for low‐frequency/low‐complexity curves) to a probability density estimate for more intricate situations. This scale‐independence facilitates displays based on non‐linear time, enabling high‐resolution accuracy of recent values, accompanied by long historical series for context. We demonstrate the functionality of this approach in the context of prediction scenarios and in the context of streaming data.     

An Illustrative Visualization Framework for 3D Vector Fields

Most 3D vector field visualization techniques suffer from the problem of visual clutter, and it remains a challenging task to effectively convey both directional and structural information of 3D vector fields. In this paper, we present a novel visualization framework that combines the advantages of clustering methods and illustrative rendering techniques to generate a concise and informative depiction of complex flow structures. Given a 3D vector field, we first generate a number of streamlines covering the important regions based on an entropy measurement. Then we decompose the streamlines into different groups based on a categorization of vector information, wherein the streamline pattern in each group is ensured to be coherent or nearly coherent. For each group, we select a set of representative streamlines and render them in an illustrative fashion to enhance depth cues and succinctly show local flow characteristics. The results demonstrate that our approach can generate a visualization that is relatively free of visual clutter while facilitating perception of salient information of complex vector fields.     

Isotropic Remeshing with Fast and Exact Computation of Restricted Voronoi Diagram

We propose a new isotropic remeshing method, based on Centroidal Voronoi Tessellation (CVT) . Constructing CVT requires to repeatedly compute Restricted Voronoi Diagram (RVD) , defined as the intersection between a 3D Voronoi diagram and an input mesh surface. Existing methods use some approximations of RVD. In this paper, we introduce an efficient algorithm that computes RVD exactly and robustly. As a consequence, we achieve better remeshing quality than approximation-based approaches, without sacrificing efficiency. Our method for RVD computation uses a simple procedure and a kd -tree to quickly identify and compute the intersection of each triangle face with its incident Voronoi cells. Its time complexity is O ( m log n ), where n is the number of seed points and m is the number of triangles of the input mesh. Fast convergence of CVT is achieved using a quasi-Newton method, which proved much faster than Lloyd's iteration. Examples are presented to demonstrate the better quality of remeshing results with our method than with the state-of-art approaches.     

Interactive Simulation of the Human Eye Depth of Field and Its Correction by Spectacle Lenses

This paper describes a fast rendering algorithm for verification of spectacle lens design. Our method simulates refraction corrections of astigmatism as well as myopia or presbyopia. Refraction and defocus are the main issues in the simulation. For refraction, our proposed method uses per-vertex basis ray tracing which warps the environment map and produces a real-time refracted image which is subjectively as good as ray tracing. Conventional defocus simulation was previously done by distribution ray tracing and a real-time solution was impossible. We introduce the concept of a blur field, which we use to displace every vertex according to its position. The blurring information is precomputed as a set of field values distributed to voxels which are formed by evenly subdividing the perspective projected space. The field values can be determined by tracing a wavefront from each voxel through the lens and the eye, and by evaluating the spread of light at the retina considering the best human accommodation effort. The blur field is stored as texture data and referred to by the vertex shader that displaces each vertex. With an interactive frame rate, blending the multiple rendering results produces a blurred image comparable to distribution ray tracing output.     

Geometry‐Aware Framebuffer Level of Detail

This paper introduces a framebuffer level of detail algorithm for controlling the pixel workload in an interactive rendering application. Our basic strategy is to evaluate the shading in a low resolution buffer and, in a second rendering pass, resample this buffer at the desired screen resolution. The size of the lower resolution buffer provides a trade‐off between rendering time and the level of detail in the final shading. In order to reduce approximation error we use a feature‐preserving reconstruction technique that more faithfully approximates the shading near depth and normal discontinuities. We also demonstrate how intermediate components of the shading can be selectively resized to provide finer‐grained control over resource allocation. Finally, we introduce a simple control mechanism that continuously adjusts the amount of resizing necessary to maintain a target framerate. These techniques do not require any preprocessing, are straightforward to implement on modern GPUs, and are shown to provide significant performance gains for several pixel‐bound scenes.     

Real‐Time Depth‐of‐Field Rendering Using Point Splatting on Per‐Pixel Layers

We present a real‐time method for rendering a depth‐of‐field effect based on the per‐pixel layered splatting where source pixels are scattered on one of the three layers of a destination pixel. In addition, the missing information behind foreground objects is filled with an additional image of the areas occluded by nearer objects. The method creates high‐quality depth‐of‐field results even in the presence of partial occlusion, without major artifacts often present in the previous real‐time methods. The method can also be applied to simulating defocused highlights. The entire framework is accelerated by GPU, enabling real‐time post‐processing for both off‐line and interactive applications.     

Detecting Symmetries and Curvilinear Arrangements in Vector Art

Understanding symmetries and arrangements in existing content is the first step towards providing higher level content aware editing capabilities. Such capabilities may include edits that both preserve existing structure as well as synthesize entirely new structures based on the extracted pattern rules. In this paper we show how to detect regular symmetries and arrangement along curved segments in vector art. We determine individual elements in the art by using the transformation similarity for sequences of sample points on the input curves. Then we detect arrangements of those elements along an arbitrary curved path. We can un-warp the arrangement path to detect symmetries near the path. We introduce novel applications inform of editing elements that are arranged along a curved path. This includes their sliding along the path, changing of their spacing, or their scale. We also allow the user to brush the elements that the system recognized along new paths.     

Packet-based Hierarchal Soft Shadow Mapping

Recent soft shadow mapping techniques based on back-projection can render high quality soft shadows in real time. However, real time high quality rendering of large penumbrae is still challenging, especially when multilayer shadow maps are used to reduce single light sample silhouette artifact. In this paper, we present an efficient algorithm to attack this problem. We first present a GPU-friendly packet-based approach rendering a packet of neighboring pixels together to amortize the cost of computing visibility factors. Then, we propose a hierarchical technique to quickly locate the contour edges, further reducing the computation cost. At last, we suggest a multi-view shadow map approach to reduce the single light sample artifact. We also demonstrate its higher image quality and higher efficiency compared to the existing depth peeling approaches.     

Interpolatory and Mixed Loop Schemes

This paper presents a new interpolatory Loop scheme and an unified and mixed interpolatory and approximation subdivision scheme for triangular meshes. The former which is C¹ continuous as same as the modified Butterfly scheme has better effect in some complex models. The latter can be used to solve the “popping effect” problem when switching between meshes at different levels of resolution. The scheme generates surfaces coincident with the Loop subdivision scheme in the limit condition having the coefficient k equal 0. When k equal 1, it will be changed into a new interpolatory subdivision scheme. Eigen‐structure analysis demonstrates that subdivision surfaces generated using the new scheme are C¹ continuous. All these are achieved only by changing the value of a parameter k. The method is a completely simple one without constructing and solving equations. It can achieve local interpolation and solve the “popping effect” problem which are the method's advantages over the modified Butterfly scheme.     

Visualization of vessel movements

We propose a geographical visualization to support operators of coastal surveillance systems and decision making analysts to get insights in vessel movements. For a possibly unknown area, they want to know where significant maritime areas, like highways and anchoring zones, are located. We show these features as an overlay on a map. As source data we use AIS data: Many vessels are currently equipped with advanced GPS devices that frequently sample the state of the vessels and broadcast them. Our visualization is based on density fields that are derived from convolution of the dynamic vessel positions with a kernel. The density fields are shown as illuminated height maps. Combination of two fields, with a large and small kernel provides overview and detail. A large kernel provides an overview of area usage revealing vessel highways. Details of speed variations of individual vessels are shown with a small kernel, highlighting anchoring zones where multiple vessels stop. Besides for maritime applications we expect that this approach is useful for the visualization of moving object data in general.