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首页> 外文期刊>IEEE transactions on multimedia >In-Network View Synthesis for Interactive Multiview Video Systems
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In-Network View Synthesis for Interactive Multiview Video Systems

机译：交互式多视图视频系统的网络内视图综合

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摘要

In multiview applications, camera views can be used as reference views to synthesize additional virtual viewpoints, allowing users to freely navigate within a 3D scene. However, bandwidth constraints may restrict the number of reference views sent to clients, limiting the quality of the synthesized viewpoints. In this work, we study the problem of in-network reference view synthesis aimed at improving the navigation quality at the clients. We consider a distributed cloud network architecture, where data stored in a main cloud is delivered to end users with the help of cloudlets, i.e., resource-rich proxies close to the users. We argue that, in case of limited bandwidth from the cloudlet to the users, re-sampling at the couldlet the viewpoints of the 3D scene (i.e., synthesizing novel virtual views in the cloudlets to be used as new references to the decoder) is beneficial compared to mere subsampling of the original set of camera views. We therefore cast a new reference view selection problem that seeks the subset of views minimizing the distortion over a view navigation window defined by the user under bandwidth constraints. We prove that the problem is NP-hard, and we propose an effective polynomial time algorithm using dynamic programming to solve the optimization problem under general assumptions that cover most of the multiview scenarios in practice. Simulation results confirm the performance gain offered by virtual view synthesis in the network.
机译：在多视图应用程序中，可以将相机视图用作参考视图，以合成其他虚拟视点，从而允许用户在3D场景中自由导航。但是，带宽限制可能会限制发送给客户端的参考视图的数量，从而限制合成视点的质量。在这项工作中，我们研究了网络参考视图综合的问题，旨在提高客户的导航质量。我们考虑一种分布式云网络体系结构，在该体系结构中，存储在主云中的数据借助小云（即靠近用户的资源丰富的代理）交付给最终用户。我们认为，在从小云到用户的带宽有限的情况下，在小枪上重新采样3D场景的视点（即，在小云中合成新颖的虚拟视图以用作对解码器的新引用）是有益的与仅对原始摄像机视图集进行二次采样相比。因此，我们提出了一个新的参考视图选择问题，该问题寻求视图的子集，以将用户在带宽限制下定义的视图导航窗口上的失真最小化。我们证明了该问题是NP难的，并且我们提出了一种有效的多项式时间算法，该算法使用动态规划来解决在实践中涵盖大多数多视图场景的一般假设下的优化问题。仿真结果证实了网络中虚拟视图综合所提供的性能提升。

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