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.

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Published
2025-06-17
DOI
https://doi.org/10.1145/3722212.3725099
Primary Topic
3D Surveying and Cultural Heritage
Type
article
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0.00
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article

Demonstrating MAST: An Efficient System for Point Cloud Data Analytics

Haitao Yuan, Z.R. Wang, Gao Cong, Han Mao Kiah et al.
3D Surveying and Cultural Heritage
article

Demonstrating MAST: An Efficient System for Point Cloud Data Analytics

Haitao Yuan, Z.R. Wang, Gao Cong, Han Mao Kiah, Jiangneng Li, Jie Wang
article en

Abstract

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.

Nanyang Technological University (SG)
Openalex Percentile: Top 80%
3D Surveying and Cultural Heritage
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Demonstrating MAST: An Efficient System for Point Cloud Data Analytics — Haitao Yuan, Z.R. Wang, et al. · (2025) | TGRS Research Map | TGRS