Graph-based parallel large scale structure from motion

作者：

Highlights：

• We proposed an robust image clustering algorithm, where images are clustered into groups of suitable size with overlap, the connectivity is enhanced with the help of an MaxST.

• We proposed a novel graph-based sub-model merging algorithm, where MinST is constructed to find accurate similarity transformations, and MHT is constructed to avoid error accumulation during the merging process.

• The time complexity is linearly related to the number of images, while most state-of-the-art algorithms are quadratic.

摘要

•We proposed an robust image clustering algorithm, where images are clustered into groups of suitable size with overlap, the connectivity is enhanced with the help of an MaxST.•We proposed a novel graph-based sub-model merging algorithm, where MinST is constructed to find accurate similarity transformations, and MHT is constructed to avoid error accumulation during the merging process.•The time complexity is linearly related to the number of images, while most state-of-the-art algorithms are quadratic.

论文关键词：Clustering,Structure from motion,Minimum spanning tree

论文评审过程：Received 24 December 2019, Revised 23 June 2020, Accepted 1 July 2020, Available online 3 July 2020, Version of Record 23 July 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107537