Published 2021 | Version v1
Publication Metadata-only

ROAD EXTRACTION AND ROAD WIDTH ESTIMATION VIA FUSION OF AERIAL OPTICAL IMAGERY, GEOSPATIAL DATA, AND STREET-LEVEL IMAGES

Grillo A.
Krylov V. A.
Moser G.
Serpico S. B.
Others:
Grillo, A.
Krylov, V. A.
Moser, G.
Serpico, S. B.

Description

Road information extraction based purely on remote sensing can be affected by occlusions of the road surface caused by trees, shadows, and buildings. We propose a multimodal fusion method that addresses road extraction and road width estimation by combining aerial imagery, monocular images taken at ground level (street-level), and geospatial data (OpenStreetMap). The method combines semantic segmentation through convolutional neural networks, Voronoi diagram processing, and graph matching.

Additional details

Identifiers Origin repository
Created:
July 5, 2023
Modified:
November 28, 2023