Multiview video is increasingly getting attention due to emerging applications such as 3DTV and immersive teleconferencing. In this paper, we present a non-stationary Hidden Markov Model (HMM) for characterizing the data rate of compressed multiview content. The states of the model correspond to different video activity levels and exhibit a Poisson state duration distribution. We derive a stable maximum likelihood algorithm for estimating the parameters of our multiview traffic model. Synthetic data generated by the model exhibits statistics that closely match those of actual multiview data. In addition, we demonstrate the high accuracy of the model in two multiview streaming applications by evaluating the frame loss rate of a constrained network buffer fed by actual and synthetic data. © 2010 IEEE.
A NON-STATIONARY HIDDEN MARKOV MODEL OF MULTIVIEW VIDEO TRAFFIC / Rossi, Lorenzo; Jacob, Chakareski; Pascal, Frossard; Colonnese, Stefania. - (2010), pp. 2921-2924. (Intervento presentato al convegno IEEE International Conference on Image Processing tenutosi a Hong Kong; Hong Kong nel SEP 26-29, 2010) [10.1109/icip.2010.5652844].
A NON-STATIONARY HIDDEN MARKOV MODEL OF MULTIVIEW VIDEO TRAFFIC
ROSSI, LORENZO;COLONNESE, Stefania
2010
Abstract
Multiview video is increasingly getting attention due to emerging applications such as 3DTV and immersive teleconferencing. In this paper, we present a non-stationary Hidden Markov Model (HMM) for characterizing the data rate of compressed multiview content. The states of the model correspond to different video activity levels and exhibit a Poisson state duration distribution. We derive a stable maximum likelihood algorithm for estimating the parameters of our multiview traffic model. Synthetic data generated by the model exhibits statistics that closely match those of actual multiview data. In addition, we demonstrate the high accuracy of the model in two multiview streaming applications by evaluating the frame loss rate of a constrained network buffer fed by actual and synthetic data. © 2010 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
