Work

Demonstrating MAST: An Efficient System for Point Cloud Data Analytics

Year: 2025

Type: conference-paper

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.

Source: Proceedings - ACM-SIGMOD International Conference on Management of Data

DOI: 10.1145/3722212.3725099

Authors: Jiangneng Li, Haitao Yuan, Jie Wang, Ziting Wang, Han Mao Kiah, Gao Cong

Institution: Nanyang Technological University

Language: English

Topic: Data Management and Algorithms

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4411374379

FWCI: 0.977

Cites: 5

Cited by: 1

Related to: 10