CAREER: Scale Variability of 3D Geometry for Computer Vision

职务名称：职业：计算机视觉中3D几何形状的尺度可变性PI：Ko Nishino机构：Drexel University随着主动和被动3D传感技术的出现，3D几何数据现在在跨越广泛学科的许多应用中发挥着至关重要的作用。然而，很少有人注意到现实世界的物体和场景是由不同尺度的几何结构组成的。例如，人脸具有少数有区别的局部表面结构，其跨越从大到小尺度的宽范围的空间范围，诸如前额、下巴、鼻子、眼睛、嘴、鼻孔、耳垂、皱纹和酒窝。这些局部结构的相对大小和空间配置共同定义了面部的特征几何形状。反过来，如果提取得当，它们会为准确描述对象或场景的几何形状添加重要信息。这项研究计划的目标是建立一个通用的理论和计算基础，分析和利用这个隐藏的三维几何尺寸-几何尺度的变化。 研究计划的核心是调查和推导表面几何形状的正式尺度空间表示，忠实地编码尺度变化的新颖的局部和全局几何表示，以及在许多重要应用中利用额外尺度相关信息的新颖计算方法。这些关键组成部分的研究推力将单独和集体使一个揭开和利用3D几何的隐藏的特征属性。该研究计划还侧重于研究几何尺度可变性在一些基本应用中的使用，包括3D匹配，配准和识别，所有这些都是使用3D几何数据的许多其他应用中的重要组成部分。该研究不仅将导致对3D几何形状的更鲁棒和有效的分析和处理，而且还将实现处理几何形状的新方法，例如将距离图像拼接在一起，就像镶嵌强度图像一样，并为3D几何数据的新用途奠定基础，例如，在外观建模中。 由于几何数据的普遍使用，预计结果将在广泛的学科中产生重大影响，特别是在国家和社会重要领域。例如，它将能够对人体器官的异常几何结构进行更精细的分析，例如使用3D内窥镜进行恢复，从而实现更准确的医疗诊断;提供丰富的判别信息，用于对数字考古中经常遇到的大量几何数据进行分类和匹配;毫无疑问，它将成为任何基于3D传感的国土安全监控应用的组成部分。几何比例可变性的使用可以远远超出这些示例，从而导致利用3D几何数据的新范例。URL：http://www.cs.drexel.edu/~kon/gscale/

Title: CAREER: Scale Variability of 3D Geometry for Computer VisionPI: Ko NishinoInstitution: Drexel UniversityWith the advent of active and passive 3D sensing techniques, 3D geometric data now play vital roles in many applications spanning a broad range of disciplines. Yet, little attention has been given to the fact that real-world objects and scenes consist of geometric structures of varying scales. For instance, a human face has a handful of discriminative local surface structures that span a wide range of spatial extents, such as the forehead, chin, nose, eyes, mouth, nostrils, earlobes, wrinkles, and dimples, from large to small scales. The relative sizes and the spatial configuration of these local structures collectively define the characteristic geometry of the face. In turn, if extracted properly, they add significant information for accurately describing the geometry of the object or scene. The goal of this research program is to establish a general theoretical and computational foundation for analyzing and exploiting this hidden dimension of 3D geometry -- the geometric scale variability. At the heart of the research program are the investigation and derivation of a formal scale-space representation of surface geometry, novel local and global geometric representations that faithfully encode the scale variability, and novel computational methods for leveraging the extra scale-related information in a number of important applications. These key componential research thrusts will individually and collectively enable one to unveil and harness the hidden characteristic properties of 3D geometry.This research program also focuses on investigating the use of geometric scale variability in a number of fundamental applications, including 3D matching, registration, and recognition, all of which serve as vital building blocks in many other applications that use 3D geometric data. The research will lead to not only more robust and efficient analysis and processing of 3D geometry, but will also enable novel approaches to handling geometry, for instance stitching together range images just like mosaicing intensity images, and set the foundation for novel use of 3D geometric data, for example, in appearance modeling. Due to the ubiquitous use of geometric data, the results are expected to have a significant impact across a broad range of disciplines, especially in nationally and societally vital domains. For instance, it will enable finer analysis of anomalous geometric structures of human organs, such as those recovered with 3D endoscopy, leading to more accurate medical diagnosis; provide rich discriminative information for sorting and matching a large collection of geometric data as often encountered in digital archaeology; and undoubtedly serve as an integral component of any 3D sensing-based surveillance application for homeland security. The use of geometric scale variability can go far beyond these examples, leading to a new paradigm for exploiting 3D geometric data.URL: http://www.cs.drexel.edu/~kon/gscale/