Because of the remarkable technological development of sensors and algorithms for point cloud data acquisition and registration, collecting point cloud data over large spaces has become more accessible than ever before. The result of this process is the generation of massive point cloud data, which can exceed the capacity of a single computer. Efficient visualization of this data is an important issue that needs to be addressed. Using big data platforms, such as Hadoop, could bring benefits in processing big point cloud data. However, due to some barriers, there have not been many studies conducted on this platform to solve problems of big point cloud data, so far. In this study, the potential and challenges of processing big point cloud data using Hadoop will be presented. Thereafter, a comprehensive solution will be proposed to overcome the limitations, which can result in the first Hadoop-based framework for fully processing massive point cloud data.
|Publication status||Published - 2020|
|Event||40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 - Daejeon, Korea, Republic of|
Duration: 2019 Oct 14 → 2019 Oct 18
|Conference||40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019|
|Country/Territory||Korea, Republic of|
|Period||19/10/14 → 19/10/18|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) government (Ministry of Science and ICT) (No. 2018R1A2B2009160).
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (No. 2018R1A2B2009160).
© 2020 40th Asian Conference on Remote Sensing, ACRS 2019: "Progress of Remote Sensing Technology for Smart Future". All rights reserved.
All Science Journal Classification (ASJC) codes
- Information Systems