A new approach to interactive viewpoint selection for volume data sets. (July 2013)

• Record Type: Journal Article
• Authors: Kim, Han Suk; Unat, Didem; Baden, Scott B; Schulze, Jürgen P
• Other Names: Kao David L guest-editor.; Wong Pak Chung guest-editor.
• Is Part Of: Information visualization. Volume 12:Number 3/4(2013)
• Page Start: 240
• Page End: 256
• Publication Date: 2013-07
• Subjects: Viewpoint selection -- Harris interest point detection -- principal component analysis; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/1473871612467631
• Languages: English
• ISSNs: 1473-8716

Abstract

Automatic viewpoint selection algorithms try to optimize the view of a data set to best show its features. They are often based on information theoretic frameworks. Although many algorithms have shown useful results, they often take several seconds to produce a result because they render the scene from a variety of viewpoints and analyze the result. In this article, we propose a new algorithm for volume data sets that dramatically reduces the running time. Our entire algorithm takes less than a second, which allows it to be integrated into real-time volume-rendering applications. The interactive performance is achieved by solving a maximization problem with a small sample of the data set, instead of rendering it from a variety of directions. We compare performance results of our algorithm to state-of-the-art approaches and show that our algorithm achieves comparable results for the resulting viewpoints. Furthermore, we apply our algorithm to multichannel volume data sets.