Ahmed, R.; Karmakar, G. C. and Dooley, L. S.
(2006).
URL: | http://ieeexplore.ieee.org/search/wrapper.jsp?arnu... |
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DOI (Digital Object Identifier) Link: | https://doi.org/10.1109/ICIP.2006.312771 |
Google Scholar: | Look up in Google Scholar |
Abstract
Embedding generic shape information into probabilistic spatio-temporal video object segmentation is of pivotal importance to achieving better segmentation, since it provides valuable perceptual clues for humans in both distinguishing and recognising objects. Recently a probabilistic spatio-temporal video object segmentation algorithm incorporating shape information has been proposed, though since it is restricted to only pixel features, the probability of a pixel belonging to a certain cluster is directly correlated with its spatial location, which theoretically limits the segmentation performance of the technique. To address this problem, this paper proposes a new probabilistic spatio-temporal video object segmentation algorithm that incorporates generic shape information based on its region. Experimental results reveal a significant performance improvement in arbitrary-shaped video object segmentation compared with other contemporary methods for a variety of standard video test sequences
Item Type: | Conference or Workshop Item |
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ISSN: | 1522-4880 |
Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
Research Group: | Centre for Research in Computing (CRC) |
Item ID: | 10560 |
Depositing User: | Laurence Dooley |
Date Deposited: | 10 Apr 2008 |
Last Modified: | 04 Oct 2016 10:08 |
URI: | http://oro.open.ac.uk/id/eprint/10560 |
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