Demonstrating MAST: An Efficient System for Point Cloud Data Analytics
The rapid growth of point cloud (PC) data calls for specialized solutions for data management and analytics. In this paper, we introduce MAST, a prototype system designed for efficient PC data analysis. MAST enables users to perform analytical queries efficiently, incorporating semantic and spatial predicates while ensuring high query accuracy. In this demonstration, we introduce the framework of the system prototype, including the storage layer, preprocessing layer, query processing layer, visualization and user feedback layer. We introduce the user interface of MAST and its workflow, and showcase the end-to-end usage of the MAST system with 2 analytical queries executed on a real PC dataset.
Authors
- Haitao Yuan (ORCID: https://orcid.org/0000-0001-6721-065X)
- Z.R. Wang
- Gao Cong (ORCID: https://orcid.org/0000-0002-4430-6373)
- Han Mao Kiah (ORCID: https://orcid.org/0000-0001-5611-0848)
- Jiangneng Li (ORCID: https://orcid.org/0000-0002-4387-5320)
- Jie Wang (ORCID: https://orcid.org/0000-0002-3879-0971)
Institutions
- Nanyang Technological University (SG)
Publication Details
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1145/3722212.3725099
- Primary Topic
- 3D Surveying and Cultural Heritage
- Type
- article
- Field-Weighted Citation Impact
- 0.00