LGT/VOT tracking performance evaluation of depth images

Haggag,H, Hossny,M, Haggag,S, Xiao,J, Nahavandi,S and Creighton,D 2014, LGT/VOT tracking performance evaluation of depth images, in SOSE 2014 : The Socio-Technical Perspective : Proceedings of the 9th International Conference on System of Systems Engineering, IEEE, Piscataway, N.J., pp. 284-288, doi: 10.1109/SYSOSE.2014.6892502.

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Title LGT/VOT tracking performance evaluation of depth images
Author(s) Haggag,H
Hossny,MORCID iD for Hossny,M orcid.org/0000-0002-1593-6296
Haggag,S
Xiao,J
Nahavandi,SORCID iD for Nahavandi,S orcid.org/0000-0002-0360-5270
Creighton,DORCID iD for Creighton,D orcid.org/0000-0002-9217-1231
Conference name System of Systems Engineering. Conference (2014 : Adelaide, South Australia)
Conference location Adelaide, South Australia
Conference dates 9-13 Jun. 2014
Title of proceedings SOSE 2014 : The Socio-Technical Perspective : Proceedings of the 9th International Conference on System of Systems Engineering
Editor(s) [Unknown]
Publication date 2014
Conference series System of Systems Engineering Conference
Start page 284
End page 288
Total pages 5
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Depth Sensors
LGT tracker
Object Tracking
Summary This paper presents object tracking in depth, RGB and normal-maps images using LGT tracker. The depth and RGB images are rendered using depth imaging plugins. A series of experiments were held to evaluate the tracker performance in tracking objects in different image sequences. The experiments conducted were from the Visual Object Tracking (VOT) challenge that was arranged in association with ICCV'13 The accuracy was chosen as the evaluation measure, where the the tracker's bounding box was compared against the ground truth bounding box. Results show that tracking object using depth images gives better results and is more accurate than tracking using either the RGB or nomal maps images.
ISBN 9781479952274
Language eng
DOI 10.1109/SYSOSE.2014.6892502
Field of Research 110999 Neurosciences not elsewhere classified
Socio Economic Objective 970101 Expanding Knowledge in the Mathematical Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, Institute of Electrical and Electronics Engineers
Persistent URL http://hdl.handle.net/10536/DRO/DU:30070517

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