序列化
计算机科学
管道(软件)
计算
平行性(语法)
互联网
并行计算
匹配(统计)
比例(比率)
分布式计算
计算机图形学(图像)
算法
万维网
操作系统
统计
数学
物理
量子力学
作者
Sameer Agarwal,Noah Snavely,Ian Simon,Steven M. Seitz,Richard Szeliski
标识
DOI:10.1109/iccv.2009.5459148
摘要
We present a system that can match and reconstruct 3D scenes from extremely large collections of photographs such as those found by searching for a given city (e.g., Rome) on Internet photo sharing sites. Our system uses a collection of novel parallel distributed matching and reconstruction algorithms, designed to maximize parallelism at each stage in the pipeline and minimize serialization bottlenecks. It is designed to scale gracefully with both the size of the problem and the amount of available computation. We have experimented with a variety of alternative algorithms at each stage of the pipeline and report on which ones work best in a parallel computing environment. Our experimental results demonstrate that it is now possible to reconstruct cities consisting of 150 K images in less than a day on a cluster with 500 compute cores.
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