English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper presents a method that automatically detects windows of different shapes, in 3D LiDAR point clouds obtained from mobileterrestrial data acquisition systems in the urban environment. The proposed method first segments out 3D points belonging to thebuilding façade from the 3D urban point cloud and then projects them onto a 2D plane parallel to the building façade. After pointinversion within a watertight boundary, windows are segmented out based on geometrical information. The window features/parametersare then estimated exploiting both symmetrically corresponding windows in the façade as well as temporally corresponding windows insuccessive passages, based on analysis of variance measurements. This unique fusion of information not only accommodates for lackof symmetry but also helps complete missing features due to occlusions. The estimated windows are then used to refine the 3D pointcloud of the building façade. The results, evaluated on real data using different standard evaluation metrics, demonstrate the efficacy aswell as the technical prowess of the method

Automatic Detection and Feature Estimation of Windows for Refining Building Facades in 3D Urban Point Clouds