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 April 2007, Honolulu, HI.
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
Actions (login may be required)
