Open AccessTDA 3D Data Model and Feature Simplification Analysis
Author(s) -
Li Ou
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1883/1/012023
Subject(s) - point cloud , topological data analysis , computer science , segmentation , representation (politics) , matlab , data mining , data structure , topology (electrical circuits) , external data representation , process (computing) , algorithm , artificial intelligence , pattern recognition (psychology) , mathematics , combinatorics , politics , political science , law , programming language , operating system
Topology data analysis (TDA) is a combination of topology and data science. The analysis process will not cause information loss. It has been widely used in various industries in recent years. However, how to display TDA data with simpler data structure is still under exploration. This paper designs and simulates a method of TDA point cloud data segmentation and classification data topology information simplification. Firstly, the point cloud data is segmented based on the region growing method. Secondly, the idea of “topological compression” is used to express the richer data information of each segmentation part with a simpler data structure; in the experimental model, the experiment is completed on the platform of MATLAB 2016 (b), and the simple and complex representation of segmented vehicle targets completely includes all the pixel positions and gray 3D data information of the vehicle.