Appearance models for computer vision

我的研究是关于自然世界视觉外观的基本问题。我们如何在数学上模拟视觉线索，如阴影、阴影、镜像反射、纹理、散焦和运动视差？我们如何开发基于这些模型的算法，并允许视觉系统对3D世界做出可靠的推断，即对物体布局和形状，表面材料和照明的推断。图像形成的物理学（即光学）已经得到了很好的研究，许多模型在不同的简单程度上存在。从计算机视觉的角度来看，挑战在于开发支持从图像中进行可靠推断的模型。在我的研究中，我采用的主要方法是识别过去被忽视的特定类型的场景和视觉问题。例如，我在高度倾斜的平面上处理表面纹理的外观，例如在光滑物体的边界或地平线上，特别是我正在研究纹理的外观如何取决于焦点。另一个问题是阴影和纹理之间的关系，以及如何在图像中区分这些线索。第三个问题是运动视差，它可以出现在各种各样的场景中，包括杂乱的场景，如森林，但也可以出现在弯曲的镜子表面，如玻璃或金属。除了单独解决这些问题之外，我的研究还将检查这些问题之间的数学和计算关系。

My research is concerned with fundamental questions about the visual appearance of the natural world.  How can we mathematically model visual cues such as shading, shadows, mirror reflections, texture, defocus, and motion parallax ?  How can we develop algorithms that are based on these models and that allow a vision system to make reliable inferences about 3D world, namely inferences about object layout and shape, surface material, and illumination.  The physics (i.e. optics) of image formation has been well studied and many models exist at  varying levels of simplicity.  The challenge from a computer vision point of view is to develop models that support reliable inferences from images.  The main approach I take in my research is to identify particular kinds of scenes and vision problems that have been neglected in the past.  For example, I am addressing the appearance of surface texture on highly slanted planes, such as at the boundary of a smooth object or at the horizon, and in particular I am examining how the appearance of texture depends on focus. Another problem is the relationship between shading and texture and how these cues can be distinguished in images.  A third problem is motion parallax which can occur in a variety of guises, included clutttered scenes such as forests, but also on curved mirror surfaces such as glass or metal.   In addition to addressing each of these problems in isolation, my research will also examine mathematical and computational relationships between these problems.