Improved autoregressive model
C. Amo-Quarm, M. Mezhoudi, Kaliappa Ravindran
Abstract
C. Amo-Quarm, M. Mezhoudi, Kaliappa Ravindran
Abstract
The autoregressive process has been used by several authors to model MPEG video traffic and attempts to capture the frame correlation as well as the Gaussian shape of the bit rate variation. However, the autoregressive process alone does not capture scene changes. In this paper, we propose an autoregressive model of order P, AR(P) + IAP (interrupted autoregressive process), to capture scene changes. We compare the model performance to that of the actual video trace, as well as the autoregressive process without scene changes.
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The autoregressive process has been used by several authors to model MPEG video traffic and attempts to capture the frame correlation as well as the Gaussian shape of the bit rate variation. However, the autoregressive process alone does not capture scene changes. In this paper, we propose an autoregressive model of order P, AR(P) + IAP (interrupted autoregressive process), to capture scene changes. We compare the model performance to that of the actual video trace, as well as the autoregressive process without scene changes.
Key concepts: Autoregressive model, STAR model, Computer science, Nonlinear autoregressive exogenous model, Gaussian process, Autoregressive integrated moving average, Process (computing), Frame (networking)