Complex Reflectance, Texture and Shape: Methods and Representations for Object Modeling

提案#:308185标题：复杂反射率，纹理和形状：对象建模的方法和表示pi: Belhumeur， peter哥伦比亚大学本研究旨在研究具有复杂反射率的对象建模技术。我们的目标是开发一种方法来恢复自然物体的形状和反射特性——由于其固有的复杂性，传统的形状重建技术（如双目立体，运动结构，光度立体，甚至激光测距仪）难以捉摸的物体。了解形状和反射率之间的相互作用对物体建模至关重要，并且在许多方面对计算机视觉领域至关重要。然而，由于获取和存储的限制，或者可能由于缺乏适当的技术，这一有前途的研究途径在过去被忽视了。最近，PI已经引入并原型化了两种用于形状重建和反射率恢复的新方法，这两种方法基本上利用了两个被忽视的物理原理。这两种方法被命名为亥姆霍兹立体视和光场重建，它们能够在不考虑物体反射率（BRDF）的情况下恢复表面形状，并且与传统的重建技术相比，它们具有许多优点。提出的研究包括新的形状重建技术，逐点构建物体模型的方法，包括它们的形状和BRDF，以及这些模型在基于图像的渲染中的应用。此外，这些重建技术将作为广泛研究BRDF的工具，以及外观随视点和光照变化的3-D纹理。与目前的形状估计技术不同，所提出的方法将产生具有几何和BRDF数据的对象模型。对象建模技术的这种新功能将在工业设计、建筑、娱乐、机器人和医学等领域受益。对重建对象、表面法线和形状的反射率函数的估计，直接导致了基于图像的建模和计算机图形应用渲染的新方法。这些建模技术将用于研究三维纹理和自然材料（包括人体皮肤）的反射特性，这将有助于产生更有效的生成外观模型，可用于安全应用（例如，人脸识别），人机交互应用，娱乐，通过视觉模拟学习，通信等。除了结果研究的应用及其通过同行评审的出版物传播外，资金将用于在三年内支持两名博士生的培训。

Proposal #: 308185Title: Complex Reflectance, Texture and Shape: Methods and Representations for Object ModelingPI: Belhumeur, PeterColumbia UniversityThis research is to investigate techniques for modeling objects with complex reflectance. Our aim is to develop methods for recovering both shape and reflectance properties of natural objects -- objects that due to their inherent complexity have proven elusive to traditional shape reconstruction techniques such as binocular stereo, structure from motion, photometric stereo, and even laser range finders. Understanding the interplay between shape and reflectance is critical to object modeling and is in many ways central to the field of computer vision. Yet this promising avenue of research has been overlooked in the past, either due to acquisition and storage limitations or, perhaps, due to a lack of appropriate techniques. Recently, the PI's have introduced and prototyped two novel methods for shape reconstruction and reflectance recovery thatessentially exploit two neglected physical principles. These two methods, named Helmholtz stereopsis and light field reconstruction, are able to recover surface shape regardless of the object's reflectance (BRDF), and they offer numerous advantages over conventional reconstruction techniques. The proposed research includes new shape reconstruction techniques, methods for constructing object models including their shape and BRDF on a point-by-point basis, and applications of these models to image-based rendering. In addition, these reconstruction techniques will serve as tools for a broad study of BRDF's in general as well as 3-D textures whose appearance varies with viewpoint and lighting. Unlike current shape estimation techniques, the proposed methods will produce object models with both geometric and BRDF data. This new capability in object modeling technology will be beneficial in areas such as industrial design, architecture, entertainment, robotics, and medicine. Estimation of the reflectance function across the reconstructed objects, surface normals, and shape, leads directly to new methods for image-based modeling and rendering for computer graphics applications. These modeling techniques will be used to study reflectance properties of 3-D textures and natural materials (including human skin), and this will help to produce more effective generative appearance models that can be used in security applications (e.g., face recognition), human computer interaction applications, entertainment, learning through visual simulation, communications, etc. In addition to the applications of the resulting research and its dissemination through peer-reviewed publications, funding will be used to support the training of two Ph.D. students over three years.