CAREER: Scale Variability of 3D Geometry for Computer Vision
CAREER: Scale Variability of 3D Geometry for Computer Vision
批准号:
0746717
负责人:
Ko Nishino
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-04-01 至 2014-03-31
中文摘要
题目:职业:计算机视觉三维几何的尺度可变性pi: Ko nishininstitution:德雷克塞尔大学随着主动和被动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比例的几何结构组成的。例如,人脸有几个具有区别性的局部表面结构,它们跨越了广泛的空间范围,如额头、下巴、鼻子、眼睛、嘴巴、鼻孔、耳垂、皱纹和酒窝,从大到小。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,它们为准确描述物体或场景的几何形状增加了重要的信息。本研究计划的目标是为分析和利用三维几何的这个隐藏维度——几何尺度变异性——建立一个一般的理论和计算基础。研究项目的核心是调查和推导表面几何的形式化尺度空间表示,忠实地编码尺度可变性的新颖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。这些关键的组件研究将单独或共同使人们能够揭示和利用3D几何的隐藏特征属性。该研究项目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、注册和识别,所有这些都是使用3D几何数据的许多其他应用的重要组成部分。这项研究不仅将带来更强大、更有效的3D几何分析和处理,还将带来处理几何的新方法,例如将距离图像拼接在一起,就像拼接强度图像一样,并为3D几何数据的新使用奠定基础,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范围内产生重大影响,特别是在国家和社会重要领域。例如,它可以对人体器官的异常几何结构进行更精细的分析,例如通过3D内窥镜检查恢复的器官,从而实现更准确的医疗诊断;为数字考古中经常遇到的大量几何数据的分类和匹配提供丰富的判别信息;毫无疑问,它是任何基于3D传感的国土安全监控应用程序的组成部分。几何尺度可变性的使用可以远远超出这些例子,导致开发3D几何数据的新范例。URL: http://www.cs.drexel.edu/ ~今敏/ gscale /
英文摘要
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/
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会议论文
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