Stefan Bruckner

VolumeShop: an interactive system for direct volume illustration

Illustrations play a major role in the education process. Whether used to teach a surgical or radiologic procedure, to illustrate normal or aberrant anatomy, or to explain the functioning of a technical device, illustration significantly impacts learning. Although many specimens are readily available as volumetric data sets, particularly in medicine, illustrations are commonly produced manually as static images in a time-consuming process. Our goal is to create a fully dynamic three-dimensional illustration environment which directly operates on volume data. Single images have the aesthetic appeal of traditional illustrations, but can be interactively altered and explored. In this paper we present methods to realize such a system which combines artistic visual styles and expressive visualization techniques. We introduce a novel concept for direct multi-object volume visualization which allows control of the appearance of inter-penetrating objects via two-dimensional transfer functions. Furthermore, a unifying approach to efficiently integrate many non-photorealistic rendering models is presented. We discuss several illustrative concepts which can be realized by combining cutaways, ghosting, and selective deformation. Finally, we also propose a simple interface to specify objects of interest through three-dimensional volumetric painting. All presented methods are integrated into VolumeShop, an interactive hardware-accelerated application for direct volume illustration.

Exploded Views for Volume Data

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve the general problem of occlusion. In many cases an object of interest is occluded by other structures. While transparency or cutaways can be used to reveal a focus object, these techniques remove parts of the context information. Exploded views, on the other hand, do not suffer from this drawback. Our approach employs a force-based model: the volume is divided into a part configuration controlled by a number of forces and constraints. The focus object exerts an explosion force causing the parts to arrange according to the given constraints. We show that this novel and flexible approach allows for a wide variety of explosion-based visualizations including view-dependent explosions. Furthermore, we present a high-quality GPU-based volume ray casting algorithm for exploded views which allows rendering and interaction at several frames per second

Style Transfer Functions for Illustrative Volume Rendering

Illustrative volume visualization frequently employs non‐photorealistic rendering techniques to enhance important features or to suppress unwanted details. However, it is difficult to integrate multiple non‐photorealistic rendering approaches into a single framework due to great differences in the individual methods and their parameters. In this paper, we present the concept of style transfer functions. Our approach enables flexible data‐driven illumination which goes beyond using the transfer function to just assign colors and opacities. An image‐based lighting model uses sphere maps to represent non‐photorealistic rendering styles. Style transfer functions allow us to combine a multitude of different shading styles in a single rendering. We extend this concept with a technique for curvature‐controlled style contours and an illustrative transparency model. Our implementation of the presented methods allows interactive generation of high‐quality volumetric illustrations.

Illustrative Context-Preserving Exploration of Volume Data

In volume rendering, it is very difficult to simultaneously visualize interior and exterior structures while preserving clear shape cues. Highly transparent transfer functions produce cluttered images with many overlapping structures, while clipping techniques completely remove possibly important context information. In this paper, we present a new model for volume rendering, inspired by techniques from illustration. It provides a means of interactively inspecting the interior of a volumetric data set in a feature-driven way which retains context information. The context-preserving volume rendering model uses a function of shading intensity, gradient magnitude, distance to the eye point, and previously accumulated opacity to selectively reduce the opacity in less important data regions. It is controlled by two user-specified parameters. This new method represents an alternative to conventional clipping techniques, sharing their easy and intuitive user control, but does not suffer from the drawback of missing context information

Enhancing Depth-Perception with Flexible Volumetric Halos

Volumetric data commonly has high depth complexity which makes it difficult to judge spatial relationships accurately. There are many different ways to enhance depth perception, such as shading, contours, and shadows. Artists and illustrators frequently employ halos for this purpose. In this technique, regions surrounding the edges of certain structures are darkened or brightened which makes it easier to judge occlusion. Based on this concept, we present a flexible method for enhancing and highlighting structures of interest using GPU-based direct volume rendering. Our approach uses an interactively defined halo transfer function to classify structures of interest based on data value, direction, and position. A feature-preserving spreading algorithm is applied to distribute seed values to neighboring locations, generating a controllably smooth field of halo intensities. These halo intensities are then mapped to colors and opacities using a halo profile function. Our method can be used to annotate features at interactive frame rates.

Illustrative context-preserving volume rendering

In volume rendering it is very difficult to simultaneously visualize interior and exterior structures while preserving clear shape cues. Very transparent transfer functions produce cluttered images with many overlapping structures, while clipping techniques completely remove possibly important context information. In this paper we present a new model for volume rendering, inspired by techniques from illustration that provides a means of interactively inspecting the interior of a volumetric data set in a feature-driven way which retains context information. The context-preserving volume rendering model uses a function of shading intensity, gradient magnitude, distance to the eye point, and previously accumulated opacity to selectively reduce the opacity in less important data regions. It is controlled by two user-specified parameters. This new method represents an alternative to conventional clipping techniques, shares their easy and intuitive user control, but does not suffer from the drawback of missing context information.

Visual Parameter Space Analysis: A Conceptual Framework

Various case studies in different application domains have shown the great potential of visual parameter space analysis to support validating and using simulation models. In order to guide and systematize research endeavors in this area, we provide a conceptual framework for visual parameter space analysis problems. The framework is based on our own experience and a structured analysis of the visualization literature. It contains three major components: (1) a data flow model that helps to abstractly describe visual parameter space analysis problems independent of their application domain; (2) a set of four navigation strategies of how parameter space analysis can be supported by visualization tools; and (3) a characterization of six analysis tasks. Based on our framework, we analyze and classify the current body of literature, and identify three open research gaps in visual parameter space analysis. The framework and its discussion are meant to support visualization designers and researchers in characterizing parameter space analysis problems and to guide their design and evaluation processes.

Semantic Layers for Illustrative Volume Rendering

Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. The specification of transfer functions is a complex task and requires expert knowledge about the underlying rendering technique. In the case of multiple volumetric attributes and multiple visual styles the specification of the multi-dimensional transfer function becomes more challenging and non-intuitive. We present a novel methodology for the specification of a mapping from several volumetric attributes to multiple illustrative visual styles. We introduce semantic layers that allow a domain expert to specify the mapping in the natural language of the domain. A semantic layer defines the mapping of volumetric attributes to one visual style. Volumetric attributes and visual styles are represented as fuzzy sets. The mapping is specified by rules that are evaluated with fuzzy logic arithmetics. The user specifies the fuzzy sets and the rules without special knowledge about the underlying rendering technique. Semantic layers allow for a linguistic specification of the mapping from attributes to visual styles replacing the traditional transfer function specification.

Result-Driven Exploration of Simulation Parameter Spaces for Visual Effects Design

Graphics artists commonly employ physically-based simulation for the generation of effects such as smoke, explosions, and similar phenomena. The task of finding the correct parameters for a desired result, however, is difficult and time-consuming as current tools provide little to no guidance. In this paper, we present a new approach for the visual exploration of such parameter spaces. Given a three-dimensional scene description, we utilize sampling and spatio-temporal clustering techniques to generate a concise overview of the achievable variations and their temporal evolution. Our visualization system then allows the user to explore the simulation space in a goal-oriented manner. Animation sequences with a set of desired characteristics can be composed using a novel search-by-example approach and interactive direct volume rendering is employed to provide instant visual feedback.

Instant volume visualization using maximum intensity difference accumulation

It has long been recognized that transfer function setup for Direct Volume Rendering (DVR) is crucial to its usability. However, the task of finding an appropriate transfer function is complex and time‐consuming even for experts. Thus, in many practical applications simpler techniques which do not rely on complex transfer functions are employed. One common example is Maximum Intensity Projection (MIP) which depicts the maximum value along each viewing ray. In this paper, we introduce Maximum Intensity Difference Accumulation (MIDA), a new approach which combines the advantages of DVR and MIP. Like MIP, MIDA exploits common data characteristics and hence does not require complex transfer functions to generate good visualization results. It does, however, feature occlusion and shape cues similar to DVR. Furthermore, we show that MIDA – in addition to being a useful technique in its own right – can be used to smoothly transition between DVR and MIP in an intuitive manner. MIDA can be easily implemented using volume raycasting and achieves real‐time performance on current graphics hardware.