Optimal Representations for Adaptive Streaming in Interactive Multiview Video Systems
Optimal Representations for Adaptive Streaming in Interactive Multiview Video Systems
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DOI：
10.1109/tmm.2017.2713644
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发表时间：
2016-09
影响因子：
7.3
通讯作者：
L. Toni;P. Frossard
中科院分区：
文献类型：
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作者：
L. Toni;P. Frossard
交互式多视图视频流（IMVS）服务允许在具有沉浸式体验的3D场景内远程导航。这可以通过发送一组参考相机视图（锚视图）来实现，客户端使用该组参考相机视图在场景中自由导航并可能合成感兴趣的附加视点。从网络的角度来看，IMVS系统中的最大挑战是向每个客户端提供最佳的锚视图集，以最大限度地提高导航质量，最小化视图切换延迟，同时满足网络约束。在自由视点系统中集成自适应流媒体解决方案提供了一个很有前途的解决方案，部署IMVS在大型和异构的情况下，只要服务器上的多视图视频表示被正确选择。因此，我们建议通过最小化总体资源需求来优化服务器上的多视图数据，同时为不同的用户提供良好的导航质量。我们提出了一个多视图自适应流媒体系统的表示集优化问题，我们表明，它是NP-难的。因此，我们引入了多视图导航段的概念，允许将视频表示集选择作为具有有限计算复杂度的整数线性规划问题。然后，我们表明，所提出的解决方案降低了计算复杂度，同时保持最优性在大多数的3D场景。最后，我们提供了不同类别用户的模拟结果，并显示了与推荐的表示集（例如，Netflix和Apple的）或基线表示选择算法，其中编码参数是针对所有相机视图先验决定的。
Interactive multiview video streaming (IMVS) services permit to remotely navigate within a 3D scene with an immersive experience. This is possible by transmitting a set of reference camera views (anchor views), which are used by the clients to freely navigate in the scene and possibly synthesize additional viewpoints of interest. From a networking perspective, the big challenge in IMVS systems is to deliver to each client the best set of anchor views that maximizes the navigation quality, minimizes the view-switching delay and yet satisfies the network constraints. Integrating adaptive streaming solutions in free-viewpoint systems offers a promising solution to deploy IMVS in large and heterogeneous scenarios, as long as the multiview video representations on the server are properly selected. Therefore, we propose to optimize the multiview data at the server by minimizing the overall resource requirements while offering a good navigation quality to the different users. We propose a representation set optimization problem for multiview adaptive streaming systems, and we show that it is NP-hard. Therefore, we introduce the concept of multiview navigation segment that permits to cast the video representation set selection as an integer linear programming problem with a bounded computational complexity. We then show that the proposed solution reduces the computational complexity, while preserving optimality in most of the 3D scenes. We finally provide simulation results for different classes of users and show the gain offered by an optimal multiview video representation selection compared to recommended representation sets (e.g., Netflix and Apple ones) or to a baseline representation selection algorithm, where the encoding parameters are decided a priori for all the camera views.