Frontiers of Information Technology & Electronic Engineering
>> 2020,
Volume 21,
Issue 10
doi:
10.1631/FITEE.1900451
A low-overhead asynchronous consensus framework for distributed bundle adjustment
Affiliation(s): College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; Cultural Heritage Institute, Zhejiang University, Hangzhou 310027, China; Key Scientific Research Base for Digital Conservation of Cave Temples, Zhejiang University, Hangzhou 310027, China; less
Received: 2019-08-30
Accepted: 2020-10-14
Available online: 2020-10-14
Next
Previous
Abstract
Generally, the (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 introduced by the additional block partitioning step and synchronous waiting. Therefore, we propose a low- consensus framework. A 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.
京公网安备 11010502051620号
