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时空立体视觉:一种基于三角测量的深度统一框架。

Spacetime stereo: a unifying framework for depth from triangulation.

作者信息

Davis James, Nehab Diego, Ramamoorthi Ravi, Rusinkiewicz Szymon

机构信息

Honda Research Institute, Mountain View, CA 94041, USA.

出版信息

IEEE Trans Pattern Anal Mach Intell. 2005 Feb;27(2):296-302. doi: 10.1109/TPAMI.2005.37.

Abstract

Depth from triangulation has traditionally been investigated in a number of independent threads of research, with methods such as stereo, laser scanning, and coded structured light considered separately. In this paper, we propose a common framework called spacetime stereo that unifies and generalizes many of these previous methods. To show the practical utility of the framework, we develop two new algorithms for depth estimation: depth from unstructured illumination change and depth estimation in dynamic scenes. Based on our analysis, we show that methods derived from the spacetime stereo framework can be used to recover depth in situations in which existing methods perform poorly.

摘要

传统上,三角测量深度是在多个独立的研究线索中进行研究的,立体视觉、激光扫描和编码结构光等方法是分别考虑的。在本文中,我们提出了一个名为时空立体视觉的通用框架,该框架统一并推广了许多先前的方法。为了展示该框架的实际效用,我们开发了两种用于深度估计的新算法:基于非结构化光照变化的深度估计和动态场景中的深度估计。基于我们的分析,我们表明,从时空立体视觉框架派生的方法可用于在现有方法表现不佳的情况下恢复深度。

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