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The Evaluation of Direct Volume Rendering-Based Uncertainty Visualization Techniques for 3D Scalar Data

Many techniques have been proposed to represent uncertainty in data visualization. However, little research has been reported on the evaluation of their effectiveness. Moreover, no studies have been conducted to evaluate direct volume rendering (DVR)-based uncertainty visualization techniques. In this paper, we present a novel method that evaluates the perceptual effectiveness of four existing and one proposed DVR-based uncertainty visualization techniques. Four types of searching tasks that include identifying the maximum uncertainty data, identifying the minimum uncertainty data, identifying the maximum scalar data and identifying the minimum scalar data have been involved in this study, and a total of twenty-eight participants have contributed to the final main user study. Our analysis suggested that the proposed linked views and interactive specification (LVIS) technique appears to be the most accurate among all techniques, although it takes the longest task completion time. For the four existing techniques, the overlays technique appears to be the most advantageous, and it takes similar task completion time as the others. We believe that these findings can provide useful guidance for future uncertainty visualization design.