Abstract
Variable bit-rate (VBR) video sources are significantly characterized by the statistics of ‘scene changes’, which determine the activity exhibited by the pictures. In a source coded with an interframe technique, in fact, this characteristic is related to the length of the emission periods having a very high bit-rate. It therefore represents a fundamental feature in evaluating performance of a network supporting video traffic. In this paper an emission process that is able to fit different activity measurements for VBR video sources characterized by a predefined bit-rate probability density function is introduced. Such a process is based on a suitable linear combination of continuous state autoregressive Markov processes. It is analyzed with respect to its capability to match the actual values of some temporal parameters which have been introduced to characterize the source. Its modeling power is compared with that of a single autoregressive Markov process. In particular is demonstrated that the process introduced here can model faster motion within a scene than a single autoregressive Markov process. Finally a case study is introduced to point out the flexibility of the proposed process.
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