Probabilistic Spatio-Temporal Video Object Segmentation using a priori Shape Descriptor

Ahmed, Rakib; Karmakar, Gour and Dooley, Laurence S. (2007). Probabilistic Spatio-Temporal Video Object Segmentation using a priori Shape Descriptor. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’07), 15-20 Apr 2007, Honolulu, HI.

DOI: https://doi.org/10.1109/ICASSP.2007.366099

Abstract

Since shape is regarded as one of the most important attributes of visualisation, it plays a pivotal role in semantic video object segmentation applications. One of the major objectives for the research community is to segment specific objects of interest from a video sequence using prescribed shape descriptors in a diverse range of applications from video surveillance and object tracking through to medical imaging. This paper addresses this challenge by presenting a new probabilistic spatio-temporal (PST) video object segmentation algorithm that incorporates a priori generic shape descriptor representations of particular objects in a sequence. The algorithm provides considerable improvement in perceptual picture quality compared with the existing PST segmentation technique, with the numerical analysis corroborating the superior subjective segmentation performance achieved

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About

• Item ORO ID
• 10511
• Item Type
• Conference or Workshop Item
• ISSN
• 1520-6149
• Academic Unit or 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)
• Depositing User
• Laurence Dooley