多视点视频业务的Poisson隐马尔可夫模型
A Poisson Hidden Markov Model for Multiview Video Traffic
摘要：
多视图视频近来已经作为一种在新颖的多媒体服务中改善用户体验的手段而出现。我们提出了一个新的随机模型来描述由多视点视频编码（MVC）可变比特率源产生的流量。为此，我们诉诸泊松隐马尔可夫模型（P-HMM），其中第一（隐藏）层表示的视频活动的演变和第二层表示的帧大小的多个编码视图。我们提出了一种方法来估计长MVC序列中的模型参数。然后，我们提出了广泛的数值模拟评估模型的能力，以产生现实的交通特性的一般类的MVC序列。然后，我们将我们的框架扩展到网络应用程序中，我们表明我们的模型能够准确地描述MVC传输中的发送方和接收方缓冲区行为。最后，我们推导出一个模型的交互式视图选择，这与我们的流量模型，能够准确地预测实际的网络负载在交互式多视图服务的用户行为。
英文摘要：
Multiview video has recently emerged as a means to improve user experience in novel multimedia services. We propose a new stochastic model to characterize the traffic generated by a Multiview Video Coding (MVC) variable bit rate source. To this aim, we resort to a Poisson Hidden Markov Model (P-HMM), in which the first (hidden) layer represents the evolution of the video activity and the second layer represents the frame sizes of the multiple encoded views. We propose a method for estimating the model parameters in long MVC sequences. We then present extensive numerical simulations assessing the model's ability to produce traffic with realistic characteristics for a general class of MVC sequences. We then extend our framework to network applications where we show that our model is able to accurately describe the sender and receiver buffers behavior in MVC transmission. Finally, we derive a model of user behavior for interactive view selection, which, in conjunction with our traffic model, is able to accurately predict actual network load in interactive multiview services.
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