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. Attached Files Name Description MIMEType Size Downloads Title LGT/VOT tracking performance evaluation of depth images Author(s) Haggag,H Hossny,M orcid.org/0000-0002-1593-6296 Haggag,S Xiao,J Nahavandi,S orcid.org/0000-0002-0360-5270 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 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) 2018 ERA Submission GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 10 Mar 2015, 16:39:18 EST Tue, 10 Mar 2015, 16:40:17 EST Tue, 10 Mar 2015, 16:40:53 EST Wed, 11 Mar 2015, 04:11:52 EST Wed, 11 Mar 2015, 05:08:53 EST Mon, 16 Mar 2015, 09:09:26 EST Mon, 16 Mar 2015, 09:10:14 EST Mon, 16 Mar 2015, 09:13:59 EST Tue, 14 Apr 2015, 16:30:24 EST Thu, 28 May 2015, 15:05:39 EST Wed, 14 Oct 2015, 14:17:14 EST Filtered Full Citation counts:   Cited 14 times in TR Web of Science Cited 16 times in Scopus Search Google Scholar Access Statistics: 512 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Tue, 10 Mar 2015, 16:40:53 EST

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