Appearance models for computer vision

我的研究涉及自然世界的视觉外观的基本问题。 我们如何对阴影、阴影、镜面反射、纹理、散焦和运动视差等视觉线索进行数学建模？ 我们如何开发基于这些模型的算法，并允许视觉系统对3D世界进行可靠的推断，即关于对象布局和形状，表面材料和照明的推断。 成像的物理学（即光学）已经得到了很好的研究，并且存在许多不同程度的简单模型。 从计算机视觉的角度来看，挑战是开发支持从图像进行可靠推断的模型。 我在研究中采取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，我正在处理高度倾斜平面上的表面纹理外观，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，它可以以各种形式出现，包括森林等杂乱的场景，也可以出现在玻璃或金属等曲面上。 除了孤立地解决这些问题之外，我的研究还将研究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.