Synthetic augmentation methods for object detection in infrared overhead imagery

Nicholas Hamilton; Adam Webb; Matt Wilder; Ben Hendrickson; Matthew Blanck; Erin Nelson; Wiley Roemer; Timothy C. Havens

doi:10.1117/12.3014274

7 June 2024 Synthetic augmentation methods for object detection in infrared overhead imagery

Nicholas Hamilton, Adam Webb, Matt Wilder, Ben Hendrickson, Matthew Blanck, Erin Nelson, Wiley Roemer, Timothy C. Havens

Author Affiliations +

Proceedings Volume 13035, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II; 130350Y (2024) https://doi.org/10.1117/12.3014274
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Geospatial intelligence is a subject with many opportunities for machine automation. Object detection is one desirable application. However, a lack of high-volume relevant datasets can make this task difficult. To combat this issue, we introduced a spin-set augmentation technique to generate synthetic training data. We used these synthetic datasets to augment the training of an object detection deep network, focusing on visible band imagery. We have continued our efforts by further testing this method on long-wave infrared imagery, including results from YOLO, SSD, and Faster R-CNN algorithms. We also introduce another synthetic augmentation technique which involves generating physics-based fully-rendered images of 3D synthetic scenery and targets and compared the rendered image performance to that of spin-sets. This paper analyzes both the spin-set and rendered image augmentation techniques in terms of object detection performance, complexity, generalizability, and explainability.

Conference Presentation

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

Citation Download Citation

Nicholas Hamilton, Adam Webb, Matt Wilder, Ben Hendrickson, Matthew Blanck, Erin Nelson, Wiley Roemer, and Timothy C. Havens "Synthetic augmentation methods for object detection in infrared overhead imagery", Proc. SPIE 13035, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II, 130350Y (7 June 2024); https://doi.org/10.1117/12.3014274

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