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引用次数: 1

摘要

一些作者已经使用自回归过程来模拟MPEG视频流量,并试图捕获帧相关性以及比特率变化的高斯形状。然而,自回归过程本身并不能捕捉到场景的变化。本文提出了一种阶数为P、AR(P) + IAP(中断自回归过程)的自回归模型来捕捉场景变化。我们将模型的性能与实际视频跟踪的性能以及在没有场景变化的情况下的自回归过程进行了比较。
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Improved autoregressive model
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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