论文标题
时间对比度变化的感知可见性模型
Perceptual Visibility Model for Temporal Contrast Changes in Periphery
论文作者
论文摘要
建模感知对于计算机图形中的许多应用程序和发展至关重要，以优化和评估内容生成技术。迄今为止，大多数工作都集中在中央（中央凹）上。但是，这对于新颖的视野展示设备（例如虚拟和增强现实耳机）不足。此外，为中央凹觉提出的感知模型不容易扩展到偏心的外围视野，在该视野中，人类感知截然不同。在本文中，我们专注于对周围视觉感知的时间方面进行建模。我们提出了新的心理物理实验，这些实验衡量了人类观察者对各个视野中不同时空刺激的敏感性。我们使用收集的数据来构建一个感知模型，以在复杂的视频内容中不同偏心率下的时间变化的可见性。最后，我们讨论，证明和评估几个可以使用我们的技术解决的问题。首先，我们展示了我们的模型如何在不分散观众注意力的情况下将新内容注入外围内容，并讨论模型与人类注意力之间的联系。其次，我们证明了如何评估和优化的效率渲染方法，以限制时间混叠的可见性。
Modeling perception is critical for many applications and developments in computer graphics to optimize and evaluate content generation techniques. Most of the work to date has focused on central (foveal) vision. However, this is insufficient for novel wide-field-of-view display devices, such as virtual and augmented reality headsets. Furthermore, the perceptual models proposed for the fovea do not readily extend to the off-center, peripheral visual field, where human perception is drastically different. In this paper, we focus on modeling the temporal aspect of visual perception in the periphery. We present new psychophysical experiments that measure the sensitivity of human observers to different spatio-temporal stimuli across a wide field of view. We use the collected data to build a perceptual model for the visibility of temporal changes at different eccentricities in complex video content. Finally, we discuss, demonstrate, and evaluate several problems that can be addressed using our technique. First, we show how our model enables injecting new content into the periphery without distracting the viewer, and we discuss the link between the model and human attention. Second, we demonstrate how foveated rendering methods can be evaluated and optimized to limit the visibility of temporal aliasing.
