Vessel Classification on UAVs using Inertial Data and IR Imagery

Date

2015-01-01

Author

Demir, H. Seckin
Akagündüz, Erdem
Pakin, S. Kubilay

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this study, a civilian ship dataset is constructed via images captured by an infrared camera on an unmanned flying vehicle. By using this dataset and synchronized inertial data (UAV altitude and orientation, gimbal angles), a vessel classification method is proposed. The method first calculates the ship base length in meters by using segmented ship image and inertial data. By fusing the descriptors obtained from the segmented ship images and estimated ship base length, vessel classification is performed.

URI

https://hdl.handle.net/11511/93764

DOI

https://doi.org/10.1109/siu.2015.7129869

Conference Name

23nd Signal Processing and Communications Applications Conference (SIU)

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

H. S. Demir, E. Akagündüz, and S. K. Pakin, “Vessel Classification on UAVs using Inertial Data and IR Imagery,” presented at the 23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Türkiye, 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/93764.