The Open UniversitySkip to content

Efficient Probabilistic Spatio-Temporal Video Object Segmentation

Ahmed, Rakib; Karmakar, Gour C. and Dooley, Laurence S. (2007). Efficient Probabilistic Spatio-Temporal Video Object Segmentation. In: 6th IEEE International Conference on Computer and Information Science (ICIS’07), 11-13 Jul 2007, Melbourne.

DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


One of the major objectives in multimedia technology is to be able to segment objects automatically from a video sequence, for a diverse range of applications from video surveillance and object tracking through to content-based video retrieval, coding and medical imaging. Probabilistic spatio-temporal (PST) video object segmentation has been shown to be of pivotal importance in achieving better segmentation, because it considers space, colour and time features conjointly in a spatio-temporal framework. Existing PST techniques however, incur high computational expense as they normally have to process large dimensional feature vectors. This paper addresses this problem by presenting a computationally efficient PST video object segmentation algorithm that has reduced dimensionality, with experimental results confirming that for various standard video test sequences, a significant reduction in computational complexity is achieved compared with the existing PST technique, without compromising perceptual picture quality

Item Type: Conference or Workshop Item
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: 10544
Depositing User: Laurence Dooley
Date Deposited: 08 Apr 2008
Last Modified: 07 Dec 2018 09:09
Share this page:


Altmetrics from Altmetric

Citations from Dimensions

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU