Research Article
Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342816, author={Jing He and Peizhuo Wang and Jiayi Zhu and Jichao Zeng}, title={Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment}, proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India}, publisher={EAI}, proceedings_a={ICSETPSD}, year={2024}, month={1}, keywords={3d modeling virtual reality technology lod technology immune genetic algorithm}, doi={10.4108/eai.17-11-2023.2342816} }
- Jing He
Peizhuo Wang
Jiayi Zhu
Jichao Zeng
Year: 2024
Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment
ICSETPSD
EAI
DOI: 10.4108/eai.17-11-2023.2342816
Abstract
Real-time 3D imaging and display technology in virtual reality technology has become a key research object; However, modern computer work has been dramatically improved compared with the past; it still cannot meet the requirements of drawing real-time complex scenes and objects. Level of detail modeling technology is the most promising technology for 3D images, which is to develop a set of models with different levels of polygonal information from the same original model describing an event or object. Based on the above background, this article puts forward the application of 3D modeling-based LOD technology in virtual reality as the research goal, studies the concept of LOD technology in detail, analyzes the QEM algorithm, and then researches and optimizes the QEM algorithm. According to the experimental research in this article, the basic algorithm used in simplifying the initial model can simplify the model to a certain extent, but the data could be better. Using an immune genetic algorithm to facilitate nodes has succeeded dramatically, saving nearly 50% of nodes and about 90% of the time based on the most straightforward optimization. However, in this case, the model cannot display details.