Targeted 3D modeling from UAV imagery

R. Abraham Martin; Benjamin K. Heiner; John D. Hedengren

doi:10.1117/12.2304436

27 April 2018 Targeted 3D modeling from UAV imagery

R. Abraham Martin, Benjamin K. Heiner, John D. Hedengren

Proceedings Volume 10645, Geospatial Informatics, Motion Imagery, and Network Analytics VIII; 106450D (2018) https://doi.org/10.1117/12.2304436
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

Reconstruction of 3D objects from UAV EO imagery yields useful information, but can be time consuming and computationally expensive. View planning reduces processing time by selecting the optimal image set needed to reconstruct a scene. This paper demonstrates how view planning is used in a targeted manner to select a subset of images from a large existing image set to model specific vehicles or structures. Potential applications of the method include enabling 3D target classification algorithms and rapid geo-location. The method could also facilitate on-board reconstruction. The view planning algorithm is tested on five different targets, and is shown to reduce processing time for target models by up to a factor of 50 with little decrease in accuracy.

Conference Presentation

Citation Download Citation

R. Abraham Martin, Benjamin K. Heiner, and John D. Hedengren "Targeted 3D modeling from UAV imagery", Proc. SPIE 10645, Geospatial Informatics, Motion Imagery, and Network Analytics VIII, 106450D (27 April 2018); https://doi.org/10.1117/12.2304436

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