Finding landmarks within settled areas using hierarchical density-based clustering and meta-data from publicly available images

作者：

Highlights：

• Automatic tools for touristic applications are highly valuable for the user

• Single-scale clustering methods are insufficient to solve real clustering problems

• Multi-scale (hierarchical) density-based clustering improves landmark detection

• The separation of inhabited population cores facilitates the clustering approach

• Increasing the dimensionality improves the results within crowded sample spaces.

摘要

•Automatic tools for touristic applications are highly valuable for the user•Single-scale clustering methods are insufficient to solve real clustering problems•Multi-scale (hierarchical) density-based clustering improves landmark detection•The separation of inhabited population cores facilitates the clustering approach•Increasing the dimensionality improves the results within crowded sample spaces.

论文关键词：Density-based clustering,K-DBSCAN,V-DBSCAN,Hierarchical clustering,Landmark detection,Tourism

论文评审过程：Received 27 September 2018, Revised 9 January 2019, Accepted 15 January 2019, Available online 16 January 2019, Version of Record 22 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.046