A. Georgopoulos

Papers

Total Citations

H-Index

About

A. Georgopoulos is a leading figure in photogrammetry and computer vision, with a focused expertise in 3D edge detection and spatial data analysis. Their most-cited work, "3D Edge Detection Based on Normal Vectors" (2024, 7 citations), represents a significant contribution to automating the extraction of geometric features from point clouds and 3D models. This research addresses a critical gap in the field: while 2D edge detection is well-established, robust automation in 3D space remains challenging. By leveraging normal vector analysis, Georgopoulos has advanced the precision and reliability of 3D feature extraction, with direct applications in cultural heritage documentation, urban modeling, and autonomous navigation. Their work is foundational for researchers and practitioners seeking to bridge photogrammetric methods with modern computer vision pipelines. Georgopoulos’s contributions continue to shape how spatial data is processed, offering new pathways for automated 3D reconstruction and analysis.