ITR/AP: Beyond Polygons and Pixels: New Paradigms for Real-Time, Physically-Based Rendering

ITR：超越多边形和像素：实时、基于物理的渲染的新范例这项研究提案的最终目标是提供实时、物理准确的合成图像，以完全交互的速度提供突破性的真实感。我们将通过将并行图形渲染的新方法与先进的、特征级别的人类视觉心理物理模型和新的图像表示相结合来实现这一点。目前，图像合成的两个极端是基于物理的渲染和实时渲染，在这种渲染中，对光反射的准确模拟提供了对场景外观的忠实预测，而在实时渲染中，容忍粗略的近似精确的模拟，以交互速率提供动态图像。在今天的工作站上计算包含间接照明、表面间相互反射和颜色溢出的高质量、物理精确的图像可能需要几个小时甚至几天的时间，渲染速度的渐进式改进将不足以弥补这一差距。我们估计，复杂场景的实时全局照明模拟可能需要比今天在多处理器工作站上多107倍的处理能力。这只能通过采用一种完全不同的方法来生成、编码和显示合成图像，这种方法分离了光反射组件的计算，并基于先进的人类视觉心理物理模型和新的图像表示。低成本、高效流水线的图形加速板已经变得非常流行，但这些体系结构只处理局部照明组件，因此无法提供全局照明效果或保证物理精度。为了解决这一缺点，我们开发了新的算法，利用这些加速板的速度进行直接照明，同时在现成的英特尔微处理器集群上并行执行全局照明计算。对于复杂的环境，我们已经将计算时间从几小时减少到几分钟，但对于实时图像合成，我们还需要另外四个数量级的加速。为了实现这一目标，我们必须开发更高级的人类视觉感知模型。目前的感知驱动的绘制方法基于人类视觉的阈值模型，这些模型预测我们区分亮度对比度、空间模式、运动和颜色的能力的极限，但不能为优化绘制操作的顺序或精度提供指导。对于我们新的感知先知，我们正在开发更高级别的视觉模型，以监控阴影和反射等场景特征对感知图像质量的重要性。然后，这些新模型将推动并行计算资源的分配，并选择合适的算法来提供“最陡峭的上升”解决方案。图像表示的新数据结构将包括照明和对比度梯度以及逐个像素的强度，以确保在所有观看条件下最佳地显示物理上准确和感知上难以区分的解决方案。这些能力将把图形模拟的科学、教育和商业应用扩展到预测可靠性和速度至关重要的视觉关键任务中。

ITR: Beyond Polygons and Pixels: New Paradigms for Real-Time, Physically-Based RenderingThe ultimate goal of this research proposal is to provide real-time, physically accurate synthetic images, delivering breakthrough realism at fully interactive rates. We will achieve this by combining new approaches for parallel graphics rendering with advanced, feature-level psychophysical models of human vision and new image representations. Currently, the two extremes of image synthesis are physically-based rendering, where accurate simulation of light reflection gives faithful predictions of the appearance of scenes, and real-time rendering, where crude approximations to accurate simulation are tolerated to provide dynamic imagery at interactive rates. High-quality, physically accurate images incorporating indirect lighting, inter-reflections between surfaces, and color bleeding can take hours or even days to compute on today's workstations, and incremental improvements to the speed of rendering will not be enough to bridge the gap. We estimate that real-time simulations of global illumination for complex scenes might require 10 7 times more processing power than we have on multi-processor workstations today. This can only be achieved by taking a radically different approach to how we generate, encode, and display synthetic images, an approach that separates computation by light reflection components and is based on advanced psychophysical models of human vision and new image representations.Low-cost, efficiently pipelined graphics accelerator boards have become extremely popular, but these architectures only process local illumination components, and thus cannot provide global illumination effects or guarantee physical accuracy. To address this shortcoming, we have developed new algorithms that exploit the speed of these accelerator boards for direct lighting while performing global illumination computations in parallel on clusters of off-the-shelf Intel microprocessors. We have reduced computation times from hours to minutes for complex environments, but for real-time image synthesis we need another four orders of magnitude speed-up.To reach this goal, we must develop more advanced models of human visual perception.Current perceptually-driven rendering methods are based on threshold models of human vision that predict the limits of our abilities to discriminate luminance contrasts, spatial patterns, motions, and colors, but provide no guidance for optimizing the order or precision of rendering operations. For our new perception oracles, we are developing higher-level visual models to monitor the importance of scene features such as shadows and reflections to perceived image quality. These new models will then drive the allocation of parallel computing resources as well as select appropriate algorithms to provide the "steepest ascent" solutions. New data structures for pictorial representation will incorporate illumination and contrast gradients as well as pixel-by-pixel intensities to ensure optimal display of physically accurate and perceptually indistinguishable solutions under all viewing conditions. These capabilities will extend the scientific, educational, and commercial application of graphical simulations into visually critical tasks where predictive reliability and speed are paramount.