Foveated graphics is a promising approach to solving the bandwidth challenges of immersive virtual and augmented reality displays by exploiting the falloff in spatial acuity in the periphery of the visual field. However, the perceptual models used in these applications neglect the effects of higher-level cognitive processing, namely the allocation of visual attention, and are thus overestimating sensitivity in the periphery in many scenarios. Here, we introduce the first attention-aware model of contrast sensitivity. We conduct user studies to measure contrast sensitivity under different attention distributions and show that sensitivity in the periphery drops significantly when the user is required to allocate attention to the fovea. We motivate the development of future foveation models with another user study and demonstrate that tolerance for foveation in the periphery is significantly higher when the user is concentrating on a task in the fovea. Analysis of our model predicts potential bandwidth savings over 9 times higher than those afforded by current models. As such, our work forms the foundation for attention-aware foveated graphics techniques.
翻译:改造后的图形是一种很有希望的方法,通过利用视觉场外空间精度的下降,解决隐蔽虚拟和放大现实显示的带宽挑战。然而,这些应用中使用的感知模型忽视了高级认知处理的影响,即视觉关注的分配,因此在许多情景中高估了边缘的敏感度。在这里,我们引入了第一个对对比敏感度的注意度模型。我们进行了用户研究,以测量不同关注分布下的敏感度,并表明当用户需要关注面部时,边缘的敏感度会显著下降。我们用另一种用户研究来激励开发未来的抚摸模型,并表明当用户集中关注胚胎的任务时,外围对腐蚀的容忍度要高得多。对我们的模型的分析预测,带宽度的潜在节省量比当前模型提供的要高9倍。因此,我们的工作为关注觉醒的微动图形技术奠定了基础。