Direct Volume Interaction for Visual Data Analysis

Direct Volume Interaction for Visual Data Analysis

Alexander Wiebel Tobias Isenberg Stefan Bruckner University of Bergen Timo Ropinski Ulm University



Natural sciences, medicine and engineering are only a small selection of application domains where volumetric data, continuous as well as scattered, are close to ubiquitous. While the visualization of such data itself is not straightforward, interaction with and manipulation of volumetric data - essential aspects of effective data analysis - pose even further challenges. Due to the three-dimensional nature of the data, it is not straightforward how to select features, pick positions, segment regions or otherwise interact with the rendering or the data themselves in an intuitive manner. In this tutorial we will present state of the art approaches and methods for addressing these challenges with a special focus on the users' analysis and interaction tasks, as well as on the application of the methods in a large variety of application domains. The tutorial will start by reviewing common classes of interaction tasks in volume visualization, motivating the need for direct interaction and manipulation, and describing the usually encountered difficulties. Interaction with visualization traditionally happens in PC-based environments with mouse and 2D displays. The second part of the tutorial discusses specific interaction methods that deal with the challenges in this context. Furthermore, an overview of the range of applications of these techniques is given to demonstrate their utility. The use of alternative paradigms for interaction with volumes is discussed in the third part. Such paradigms, e.g. in the context of touch interfaces or immersive environments, provide novel opportunities for volume exploration and manipulation, but also pose specific challenges themselves. The last part completes the tutorial's scope by a treatment of higher-level interaction techniques guiding users in navigation and exploration of the data using automatic or semi-automatic methods for identifying relevant parameter ranges. Such techniques employ additional, sometimes workflow-specific, information to assist in choosing effective volume visualization techniques and related attributes.


	title={Direct Volume Interaction for Visual Data Analysis},
	author={Wiebel, Alexander and Isenberg, Tobias and Bruckner, Stefan and Ropinski, Timo},