Wang, Jing, Xu, Zhijie and Xu, Qiang (2009) Video Volume Segmentation for Event Detection. In: Computer Graphics, Imaging & Visualization, new advances and trends. IEEE Computer Society, London, UK, pp. 311-316. ISBN 9780769537894
|PDF - Accepted Version |
Download (3942kB) | Preview
Video processing for surveillance and security applications has become a research hotspot in the last decade. This paper reports a research into volume-based segmentation techniques for video event detection. It starts with an introduction of the structure in 3D video volumes denoted by spatio-temporal features extracted from video footages. The focus of the work is on devising an effective and efficient 3D segmentation technique suitable to the volumetric nature of video events through deploying innovative 3D clustering methods. It is supported by the design and experiment on the 3D data compression techniques for accelerating the pre-processing of the original video data. An evaluation on the performance of the developed methods is presented at the end.
|Item Type:||Book Chapter|
|Additional Information:||Copyright © 2009 IEEE. Reprinted from Proceedings of 2009 sixth International Conference on Computer Graphics, Imaging and Visualization. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Huddersfield’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to firstname.lastname@example.org|
|Subjects:||T Technology > T Technology (General)|
|Schools:||School of Computing and Engineering|
School of Computing and Engineering > Computer Graphics, Imaging and Vision Research Group
|Depositing User:||Jing Wang|
|Date Deposited:||11 May 2010 10:14|
|Last Modified:||05 Jan 2011 12:50|
Downloader CountriesMore statistics for this item...
Item control for Repository Staff only: