Motion Vector Recovery With Gaussian Process Regression

TitleMotion Vector Recovery With Gaussian Process Regression
Publication TypeConference Paper
Year of Publication2011
AuthorsAsheri, H., H. R. Rabiee, and M. H. Rohban
Conference NameInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Date Published05/2011
Conference LocationPrague, Czech Republic
ISBN Number978-1-4577-0539-7
KeywordsBayesian estima- tion, Error concealment, Gaussian process regression, Motion vector recovery
AbstractIn this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem of estimating the lost motion vectors is modelled as a kernel construction problem in a Bayesian framework. First, to describe the similarity between the neighboring motion vectors, a kernel function is defined. Then the parameters of the kernel function is estimated as the coefficients of a linear Bayesian estimator. The experimental results verify the superiority of the proposed algorithm over the conventional and state of the art motion vector concealment methods. Moreover, noticeable improvements on both objective and subjective measures, on videos with heavy packet loss rates have been achieved.