Parallel Structure from Motion from Local Increment to Global Averaging

28 Feb 2017 Siyu Zhu Tianwei Shen Lei Zhou Runze Zhang Jinglu Wang Tian Fang Long Quan

In this paper, we tackle the accurate and consistent Structure from Motion (SfM) problem, in particular camera registration, far exceeding the memory of a single computer in parallel. Different from the previous methods which drastically simplify the parameters of SfM and sacrifice the accuracy of the final reconstruction, we try to preserve the connectivities among cameras by proposing a camera clustering algorithm to divide a large SfM problem into smaller sub-problems in terms of camera clusters with overlapping... (read more)

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