Semantic and Geometric Fusion for Object-Based 3D Change Detection in LiDAR Point Clouds

Semantic and Geometric Fusion for Object-Based 3D Change Detection in LiDAR Point Clouds

Accurate three-dimensional change detection is essential for monitoring dynamic environments such as urban areas, infrastructure, and natural landscapes. Point-based methods are sensitive to noise and lack spatial coherence, while object-based approaches rely on clustering, which can miss fine-scale...

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Bibliographic Details
Main Authors: Abderrazzaq Kharroubi, Fabio Remondino, Zouhair Ballouch, Rafika Hajji, Roland Billen
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Remote Sensing
Subjects:
3D change detection
point clouds
semantic segmentation
cut-pursuit
object-based
point-based
Online Access:https://www.mdpi.com/2072-4292/17/7/1311
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