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A low-overhead asynchronous consensus framework for distributed bundle adjustment

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Abstract

Generally, the distributed bundle adjustment (DBA) method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer. However, the performance considerably degrades owing to the overhead introduced by the additional block partitioning step and synchronous waiting. Therefore, we propose a low-overhead consensus framework. A partial barrier based asynchronous method is proposed to early achieve consensus with respect to the faster worker nodes to avoid waiting for the slower ones. A scene summarization procedure is designed and integrated into the block partitioning step to ensure that clustering can be performed on the small summarized scene. Experiments conducted on public datasets show that our method can improve the worker node utilization rate and reduce the block partitioning time. Also, sample applications are demonstrated using our large-scale culture heritage datasets.

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Authors

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Correspondence to Chang-yu Diao.

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Project supported by the Key R&D Program of Zhejiang Province, China (No. 2018C03051) and the Key Scientific Research Base for Digital Conservation of Cave Temples of the National Cultural Heritage Administration, China

Contributors

Chang-yu DIAO, Wei XING, and Dong-ming LU guided the research. Chang-yu DIAO and Zhuo-hao LIU designed the research. Zhuo-hao LIU drafted the manuscript. Changyu DIAO helped organize the manuscript. Zhuo-hao LIU revised and finalized the paper.

Compliance with ethics guidelines

Zhuo-hao LIU, Chang-yu DIAO, Wei XING, and Dongming LU declare that they have no conflict of interest.

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Liu, Zh., Diao, Cy., Xing, W. et al. A low-overhead asynchronous consensus framework for distributed bundle adjustment. Front Inform Technol Electron Eng 21, 1442–1454 (2020). https://doi.org/10.1631/FITEE.1900451

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  • DOI: https://doi.org/10.1631/FITEE.1900451

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