A new approach to interactive viewpoint selection for volume data sets

作者：Kim Han Suk^*; Unat Didem; Baden Scott B; Schulze Juergen P

来源：Information Visualization, 2013, 12(3-4): 240-256.

DOI：10.1177/1473871612467631

• Viewpoint selection
• Harris interest point detection
• principal component analysis

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.

• 出版日期2013-7