VISUALIZATION:Manipulating Volumes: A New Paradigm for Advanced Volume Visualization

可视化:操作体积:高级体积可视化的新范式

基本信息

  • 批准号:
    0118760
  • 负责人:
  • 金额:
    $ 33.92万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2001
  • 资助国家:
    美国
  • 起止时间:
    2001-09-15 至 2006-08-31
  • 项目状态:
    已结题

项目摘要

As 3D volume data becomes more prevalent from simulations and sensing equipment, and as volume rendering APIs are becoming available in software and hardware implementations, the need to manipulate volume models arises. However, the work on manipulating volume models for analysis and computer graphics applications is sparse. The few methods that are available are computationally expensive and non-intuitive. This project avoids these problems by using volumetric skeletons to control manipulation. The skeleton acts as a ubiquitous data structure for volumes and allows manipulation in a much more intuitive and general manner. The skeleton is computed from the actual volume with a reversible thinning procedure based upon the distance transform. The skeletal points are connected and arranged in a skeleton-tree structure. The key to this process is the reconstruction phase that maps the sampled voxels around the skeleton-tree. The skeleton is an intuitive mechanism for manipulation. For example, a user can deform the skeleton to create the corresponding deformations in the volume. The skeleton-tree allows the user to reshape volumes and create new visualizations. Among other things, this allows culling sections of a volume logically, morphing volumes to simulate changes in a 3D feature over time, detecting collisions for interactive volume-based virtual reality applications, and volume animation and volume graphics (mimicking the standard graphics pipeline with volumes). Because skeletons can be generated hierarchically, they can be used to perform a variety of tasks including volume smoothing and level-of-detail representation.The goal of this project is to extend and fundamentally enhance previous research in volume skeletonization. It will develop a full range of robust skeletal algorithms and interactive tools. The researchers will investigate the exciting new visualization applications of the parameter-based volume skeleton. This should have a wide impact in the visualization and computer graphics communities.
随着3D体数据在模拟和传感设备中变得越来越普遍,并且随着体绘制API在软件和硬件实现中变得可用,需要操纵体模型。然而,操纵体模型的分析和计算机图形应用的工作是稀疏的。现有的几种方法计算量大,而且不直观。这个项目通过使用体积骨架来控制操纵来避免这些问题。骨架充当体积的普遍存在的数据结构,并允许以更直观和通用的方式进行操作。骨架计算从实际体积与可逆细化过程的基础上的距离变换。骨架点连接在一起,并以一种树形结构排列。这个过程的关键是重建阶段,它将采样的体素映射到树的周围。骨骼是一种直观的操纵机制。例如,用户可以使骨架变形以在体积中创建对应的变形。该虚拟树允许用户重塑体积并创建新的可视化。除其他外,这还允许逻辑地剔除体积的部分、变形体积以模拟3D特征随时间的变化、检测基于体积的交互式虚拟现实应用程序的碰撞以及体积动画和体积图形(模仿具有体积的标准图形管道)。由于骨架可以分层生成,它们可以用来执行各种任务,包括体积平滑和细节层次representation.The项目的目标是扩展和从根本上提高以前的研究在体积crossonization。它将开发一套完整的、强大的骨架算法和交互式工具。研究人员将研究基于参数的体积骨架的令人兴奋的新可视化应用。这应该在可视化和计算机图形社区中产生广泛的影响。

项目成果

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Deborah Silver其他文献

fMRI Brain Image Retrieval Based on ICA Components
基于ICA组件的fMRI脑图像检索

Deborah Silver的其他文献

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{{ truncateString('Deborah Silver', 18)}}的其他基金

Collaborative Research: Workshop Proposal - Developing STEM Master's IDPs as an Essential Tool in Workforce Development
合作研究:研讨会提案 - 开发 STEM 硕士 IDP 作为劳动力发展的重要工具
  • 批准号:
    1940221
  • 财政年份:
    2020
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Standard Grant
Science Master's Program: Fueling Innovation in New Jersey Through Graduate Education
科学硕士课程:通过研究生教育推动新泽西州的创新
  • 批准号:
    1011202
  • 财政年份:
    2010
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Standard Grant
CI-TEAM Demonstration Project: Developing Scientific Visualization Literacy for Cybterinfrastructure Training
CI-TEAM示范项目:培养网络基础设施培训的科学可视化素养
  • 批准号:
    0753176
  • 财政年份:
    2008
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Standard Grant
Illustrative Deformation
说明性变形
  • 批准号:
    0702407
  • 财政年份:
    2007
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Continuing Grant
SGER: Measuring the Influence of Spatial Ability in Data Visualization Comprehension
SGER:测量空间能力对数据可视化理解的影响
  • 批准号:
    0503680
  • 财政年份:
    2004
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Standard Grant
ITR: Associative Mining of Large Datasets
ITR:大型数据集的关联挖掘
  • 批准号:
    0082634
  • 财政年份:
    2000
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Continuing Grant
RIA: Towards Robust Geometric Computations
RIA:迈向稳健的几何计算
  • 批准号:
    8909197
  • 财政年份:
    1989
  • 资助金额:
    $ 33.92万
  • 项目类别:
    Standard Grant

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