Simplifying complex landmark models with holes for 3D maps: a topological perception-based approach

Yuan Ding, Dongming Chen, Sisi Zlatanova, Mingguang Wu*, Kai Cao, Yongze Song, Yingbao Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Landmarks serve as critical reference points for determining spatial orientations. Owing to the complexity and diversity of the shapes of landmark buildings, numerous fine visual details can hinder the clear identification of three-dimensional (3D) landmark models, posing a challenge for their automatic generation. To address this issue, we propose a method based on topological perception to simplify 3D landmark models, focusing on enhancing global perception features by exaggerating topology-related features. This method involves three key steps: voxelization, hole exaggeration and model generation. We evaluated the effectiveness of exaggeration and conducted a quantitative analysis of its degree of application in landmark buildings. The results demonstrate that topology-based exaggeration significantly improves the perception of 3D landmark models, and the degree of exaggeration is inversely correlated with the proportion of topology-related visual features in the models. Furthermore, a comparative analysis of four commonly used simplification algorithms shows that our method outperforms the other methods across five key evaluation metrics.

Keywords

  • 3D landmark
  • model simplification
  • topological perception

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