DocumentCode
714367
Title
Vessel classification on UAVs using inertial data and IR imagery
Author
Demir, H. Seckin ; Akagunduz, Erdem ; Kubilay Pakin, S.
Author_Institution
ASELSAN, MGEO, Ankara, Turkey
fYear
2015
fDate
16-19 May 2015
Firstpage
499
Lastpage
502
Abstract
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.
Keywords
autonomous aerial vehicles; image classification; image segmentation; infrared imaging; IR imagery; UAV; civilian ship dataset; infrared camera; segmented ship image; ship base length; synchronized inertial data; unmanned flying vehicle; vessel classification; Augmented reality; Cameras; Computer vision; Histograms; Image segmentation; Marine vehicles; Vehicles; inertial data; infrared imaging; vessel classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location
Malatya
Type
conf
DOI
10.1109/SIU.2015.7129869
Filename
7129869
Link To Document