With increasing urbanization, flooding is a major challenge for many cities today. Based on
forecast precipitation, topography, and pipe networks, flood simulations can provide early …

Edges in mobile light detection and ranging (lidar) point clouds are important for many
applications but usually overlooked. In this letter, we propose a fast edge extraction method …

Geometric feature detection on surfaces is a crucial task for the characterization and
understanding of geometry shapes. In this paper, we present a robust and reliable approach …

In this paper, a novel segmentation and recognition approach to automatically extract street
lighting poles from mobile LiDAR data is proposed. First, points on or around the ground are …

Signals, such as point clouds captured by light detection and ranging sensors, are often
affected by highly reflective objects, including specular opaque and transparent materials …

Given the high frequency and major impact of flood events, decision-makers are in urgent
need to have tools allowing them to predict or assess the impact of flood events on the …

This paper proposes a building façade contouring method from LiDAR (Light Detection and
Ranging) scans and photogrammetric point clouds. To this end, we calculate the confidence …

Extraction of individual façades from building point clouds collected by ground-based LiDAR
is vital for urban mapping and modeling. It is a challenging task due to the complexity of …

Windows, as key components of building facades, have received increasing attention in
facade parsing. Convolutional neural networks have shown promising results in window …

This letter presents a 3-D object matching framework to support information extraction
directly from 3-D point clouds. The problem of 3-D object matching is to match a template …