Sung Kwon On
ABSTRACT
In this paper, a novel pose estimation algorithm is proposed specifically for maneuvering airplanes in the air. The algorithm consists of two main stages. The first stage involves semantic segmentation of a monocular input image of a flying airplane, where the entire captured area serves as feature points for the airplane, which are typically small in the image. The second stage focuses on the 3D pose estimation of the segmented image using projective registration. Since airplanes have unique characteristics and there is a scarcity of airplane-specific datasets, a custom dataset is generated for the experiments. Unreal Engine 4, a 3D computer graphics game engine renowned for its realistic simulations, is employed for this purpose. Experimental results demonstrate the suitability of the algorithm for 3D pose estimation of airplanes, providing valuable information for studying autonomous control of airplanes.
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Index Terms
- Monocular 3D Pose Estimation of Very Small Airplane in the Air
Index terms have been assigned to the content through auto-classification.
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