TY - JOUR
T1 - Simplifying complex landmark models with holes for 3D maps
T2 - a topological perception-based approach
AU - Ding, Yuan
AU - Chen, Dongming
AU - Zlatanova, Sisi
AU - Wu, Mingguang
AU - Cao, Kai
AU - Song, Yongze
AU - Yang, Yingbao
N1 - Publisher Copyright:
© 2025 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - 3D landmark
KW - model simplification
KW - topological perception
UR - https://www.scopus.com/pages/publications/105008960896
U2 - 10.1080/13658816.2025.2512222
DO - 10.1080/13658816.2025.2512222
M3 - 文章
AN - SCOPUS:105008960896
SN - 1365-8816
JO - International Journal of Geographical Information Science
JF - International Journal of Geographical Information Science
ER -