Deep learning-based shadow detection in aerial images using synthetically generated scenes

Taci Kucukpinar; Deniz Kavzak Ufuktepe; Jaired Collins; Joshua Fraser; Timothy Krock; Andrew Buck; Derek T. Anderson; Richard D. Massaro; Kannappan Palaniappan

doi:10.1117/12.3027164

10 June 2024 Deep learning-based shadow detection in aerial images using synthetically generated scenes

Taci Kucukpinar, Deniz Kavzak Ufuktepe, Jaired Collins, Joshua Fraser, Timothy Krock, Andrew Buck, Derek T. Anderson, Richard D. Massaro, Kannappan Palaniappan

Author Affiliations +

Proceedings Volume PC13037, Geospatial Informatics XIV; PC1303707 (2024) https://doi.org/10.1117/12.3027164
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

Shadows in aerial images can hinder the performance of various vision tasks, including object detection and tracking. Shadow detection networks see a reduction in performance in mid-altitude wide area motion imagery (WAMI) data since they lack the related data for training. Aerial WAMI data collection is a challenging task, and the variety of weather conditions that can be captured is limited. Moreover, obtaining accurate ground truth shadow masks for these images is difficult, where manual methods are infeasible and automatic techniques suffer from inaccuracies. We are leveraging the advanced rendering capabilities of Unreal Engine to produce city-scale synthetic aerial images. Unreal Engine can provide precise ground-truth shadow masks and cover diverse weather and lighting conditions. We further train and evaluate an existing shadow detection network with our synthetic data to improve the performance on real WAMI datasets.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Taci Kucukpinar, Deniz Kavzak Ufuktepe, Jaired Collins, Joshua Fraser, Timothy Krock, Andrew Buck, Derek T. Anderson, Richard D. Massaro, and Kannappan Palaniappan "Deep learning-based shadow detection in aerial images using synthetically generated scenes", Proc. SPIE PC13037, Geospatial Informatics XIV, PC1303707 (10 June 2024); https://doi.org/10.1117/12.3027164

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