A low-overhead asynchronous consensus framework for distributed bundle adjustment  

作　　者：Zhuo-hao LIU Chang-yu DIAO Wei XING Dong-ming LU 

机构地区：[1]College of Computer Science and Technology,Zhejiang University,Hangzhou 310027,China [2]Cultural Heritage Institute,Zhejiang University,Hangzhou 310027,China [3]Key Scientific Research Base for Digital Conservation of Cave Temples,Zhejiang University,Hangzhou 310027,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2020年第10期1442-1454,共13页信息与电子工程前沿（英文版）

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

摘　　要：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.

关 键 词：STRUCTURE-FROM-MOTION Distributed bundle adjustment OVERHEAD Asynchronous consensus Partial barrier Bipartite graph summarization 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]