Ahmed, Rakib; Karmakar, Gour C. and Dooley, Laurence S.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1109/ICIP.2007.4379579|
|Google Scholar:||Look up in Google Scholar|
Embedding textural information into the probabilistic spatio-temporal (PST) video object segmentation is very important for achieving better segmentation, since this is one of the key perceptual attributes of any object. Existing video segmentation techniques however, ignore this feature because of the underlying difficulty in defining and hence characterizing a texture, which theoretically limits their segmentation performance. To address this problem, this paper proposes a new video object segmentation algorithm that involves a strategy to seamlessly incorporate texture information as a pixel feature in the PST framework. Experimental results for a variety of standard test sequences reveal a significant performance improvement in the quality of the video object segmentation achieved in comparison with the original PST method.
|Item Type:||Conference Item|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Laurence Dooley|
|Date Deposited:||02 Apr 2008|
|Last Modified:||04 Oct 2016 10:08|
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