Collaborative Research: Visual Information about surface curvature from patterns of image shading and contours

在我们的日常生活中，我们感知物体三维形状的能力通常被认为是理所当然的，但人类和计算机视觉的研究人员都没有详细解释这是如何实现的。虽然物体是由木头、玻璃或金属等有形物质组成的，但我们对它们的感知是基于光的模式。因此，一个充分的感知理论必须能够解释光的模式如何能够独特地指定视觉环境的3D结构。该研究项目将研究物体形状的视觉感知，重点是了解人类视觉系统如何处理和解释有关物体三维特性的信息。更好地理解3D视觉可以提供许多实际应用。例如，它可以显著改善视觉引导机器人或自动驾驶汽车的设计。这对于制造假肢装置也很重要，可以帮助盲人在运动时避开潜在的障碍物，或者检测产生跌倒危险的光滑表面的存在。从阴影中计算三维形状的分析已经研究了50多年，但尽管有广泛的跨学科范围，它已经取得了相对较小的成功。一个可能的原因是，研究人员通常通过对光在自然环境中的行为做出不切实际的假设来简化问题。这使得推导数学解更容易，但严重限制了结果分析的通用性。在目前的工作中，研究者将包括许多在这一领域中通常被忽视的光学效应，包括投射阴影、表面间反射、各向异性反射、光透射和多种照明模式。他们还将对每种条件下的亮度场进行详细测量，以发现在场景参数变化时相对不变的属性。这项工作将主要集中在定性表面特征上，如凸起、酒窝、山脊、山谷和鞍形，以及它们如何与类似的图像着色定性模式相对应。将进行大量的心理物理实验，以证明1)观察者对三维表面结构的判断如何受到图像阴影模式的影响；2)这些判断对表面材料和光照模式变化的稳定性；3)即使所有其他方面的阴影都被移除，眼睛上光强度的平滑变化如何提供有关3D形状的信息。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Our ability to perceive the 3D shapes of objects is generally taken for granted in our day-to-day experiences, but a detailed explanation of how that is possible has eluded researchers in both human and computer vision. Whereas objects are composed of tangible substances such as wood, glass or metal, our perceptions of them are based on patterns of light. Thus, an adequate theory of perception must be able to explain how patterns of light can uniquely specify the 3D structure of the visual environment. This research project will study the visual perception of object shape, with a focus on understanding how the human visual system processes and interprets information about the three-dimensional properties of objects. A better understanding of 3D vision could provide many practical applications. For example, it could lead to dramatic improvements in the design of visually guided robots or autonomous vehicles. It could also be important for building prosthetic devices for the blind to avoid potential obstacles during locomotion or to detect the presence of slippery surfaces that create a danger of falling.The computational analysis of 3D shape from shading has been studied for over 50 years but despite the broad interdisciplinary scope it has had relatively minimal success. One possible reason is that researchers have typically simplified the problem by making unrealistic assumptions about how light behaves in the natural environment. This makes it easier to derive mathematical solutions, but severely limits the generality of the resulting analyses. In the present work, the investigators will include many of the optical effects that have typically been ignored in this domain, including cast shadows, surface inter-reflections, anisotropic reflections, light transmission, and multiple patterns of illumination. They will also perform detailed measurements of the luminance field in each condition to discover properties that are relatively invariant over changes in scene parameters. The work will focus primarily on qualitative surface features, such as bumps, dimples, ridges, valleys, and saddles, and how they correspond to similar qualitative patterns of image shading. Numerous psychophysical experiments will be conducted to document 1) how observers’ judgments of 3D surface structure are influenced by the pattern of image shading; 2) the stability of these judgments over changes in surface materials and patterns of illumination; and 3) how smooth variations of light intensity on the eye provide information about 3D shape, even when all other aspects of shading have been removed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.