Dynamic 2D/3D Registration
Dynamic 2D/3D Registration
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DOI：
10.2312/egt.20141021
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Sofien Bouaziz;A. Tagliasacchi;M. Pauly
中科院分区：
文献类型：
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作者：
Sofien Bouaziz;A. Tagliasacchi;M. Pauly
图像和几何配准算法是许多计算机图形学和计算机视觉系统的重要组成部分。随着微软Kinect或华硕Xtion Live等RGB-D传感器的最新技术进步，结合2D图像和3D几何图形配准的稳健算法已成为一个活跃的研究领域。本课程的目标是介绍2D/3D配准算法的基础知识，并为设计基于RGB-D设备的计算机视觉和计算机图形系统提供理论解释和实用工具。为了说明该理论并展示其实际意义，我们简要讨论了三个应用：刚性扫描、非刚性建模和实时人脸跟踪。我们的课程面向具有计算机图形学和/或计算机视觉背景的研究人员和计算机图形从业人员。最新版本的课程笔记以及幻灯片和源代码可在http://lgg.epfl.ch/2d3dRegistration.上找到
Image and geometry registration algorithms are an essential component of many computer graphics and computer vision systems. With recent technological advances in RGB-D sensors, such as the Microsoft Kinect or Asus Xtion Live, robust algorithms that combine 2D image and 3D geometry registration have become an active area of research. The goal of this course is to introduce the basics of 2D/3D registration algorithms and to provide theoretical explanations and practical tools to design computer vision and computer graphics systems based on RGB-D devices. To illustrate the theory and demonstrate practical relevance, we briefly discuss three applications: rigid scanning, non-rigid modeling, and realtime face tracking. Our course targets researchers and computer graphics practitioners with a background in computer graphics and/or computer vision. An up-todate version of the course notes as well as slides and source code can be found at http://lgg.epfl.ch/2d3dRegistration.