Improved QEM simplification algorithm based on local area feature information constraint

• Published in: Chinese Automation Congress (Online) pp. 6137 - 6142
• Main Authors: Pan, Hongbin, Xiao, Xinghui, Huang, Ziwei, Peng, Siqi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25.11.2022
• Subjects: Bending; Feature extraction; feature preservation; Image color analysis; Image edge detection; improved quadratic error metric; Measurement uncertainty; Mesh simplification; Q-factor; triangular mesh model; Visualization
• ISSN: 2688-0938
• DOI: 10.1109/CAC57257.2022.10054862

To address the issue that the traditional Quadric Error Metrics (QEM) simplification algorithm cannot effectively maintain the two crucial visual features of model details and edges, this paper improved the algorithm and proposed a simplification algorithm based on the information constraint of model local area features. The algorithm considered the changes in the average area of the neighborhood grid, the bending degree of the region, and the quality factor of the grid before and after grid simplification, and the amount of information from these changes is combined with the quadratic error measure to form a composite simplification error value. A simpler detection scheme is also given based on the characteristics of the model boundaries and sharp feature areas. The detection results are used as one of the conditions for simplification to avoid oversimplification of the model detail feature areas and protection of the model edges. The experimental findings demonstrate that, compared to the QEM simplification algorithm, this algorithm successfully suppressed the rise in simplification error while retaining model detail characteristics, improving the quality of the simplified model mesh.