Saliency-guided Graphics and Visualization

点击翻译按钮获取中文摘要

Saliency-Guided Graphics and VisualizationVisual data is growing at an incredible rate due to advances in acquisition, modeling, and simulation technologies. This is posing significant challenges in its processing, display, and comprehension. Current graphics and visualization systems effectively assume a default; that every piece of data is equally important. As the data and displays get larger, visually finding useful information is becoming ever more challenging amidst the visual clutter. This research improves on the default uniform importance by associating every geometric primitive with a salience, an indication of its visual importance, and uses it to design and guide the rendering process. This research draws upon prior work in visual perception, vision, graphics, and scientific visualization and not only addresses how to present data but also what parts of the data to present for effective and compelling visual communication. This research involves advances in algorithms, tools, and techniques to generate effective visual content to facilitate comprehension and efficient rendering.This research centers on defining and using saliency in graphics and visualization and involves developing a suite of methods for computing and assigning saliency to visual data. The investigators study how saliency can guide the rendering process to generate compelling visual content and to allocate computational and rendering resources where they have the most visual impact. The research involves rigorously validating saliency models through user studies using eye tracking and comparing them to human salience judgments. These tasks are in the driving application domains of computational biology and high-energy physics. Compelling scientific visual content has the potential to impact science education besides enhancing the accessibility of science to the common public.