Understanding the Differences in Shape Cognition Between Physical and Virtual Scenes

人们在科学可视化中使用3D图形有相当多的经验，但很少了解这些3D图形的哪些方面给我们带来了最大的感知好处。因此，我们不知道如何优化和改进我们对这个工具的使用。在这个项目中，pi将执行人体受试者测试，以测试各种深度线索对3D场景感知的有效性，并量化感知深度线索在合成场景和物理模型呈现的“真实”场景中的有效性差异。这些发现将对交互式计算机图形学和科学可视化产生重大影响，特别是对虚拟现实，在没有任何严格的科学知识的情况下，大量的精力和金钱被投入到生成逼真的合成场景中，最令人信服的现实场景线索到底是什么。这个项目应该提供一些答案。

People have considerable experience using 3D graphics in scientific visualization, but very little understanding of exactly what aspects of those 3D graphics give us the most perceptual benefit. As a consequence, we do not understand how to optimize and improve our use of this tool. In this project, the PIs will perform human-subject tests to test the effectiveness of various depth cues on the perception of 3D scenes, and to quantify the difference in effectiveness between perceptual depth cues in synthetic scenes and in "real" scenes as presented by physical models. The findings will have significant implications for interactive computer graphics and scientific visualization in general, and for virtual reality in particular, where much effort and money are being invested to generate realistic synthetic scenes without any rigorous scientific knowledge of what the most convincing realistic-scene cues really are. This project should supply some of the answers.