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首页> 外文期刊>Multimedia, IEEE Transactions on >Delay-Cognizant Interactive Streaming of Multiview Video With Free Viewpoint Synthesis
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Delay-Cognizant Interactive Streaming of Multiview Video With Free Viewpoint Synthesis

机译：具有自由视点合成的多视点视频的时延感知交互式流

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摘要

In interactive multiview video streaming (IMVS), a client receives and observes one of many available viewpoints of the same scene and periodically requests from the server view switches to neighboring views, as the video is played back in time uninterruptedly. One key technical challenge is to design a frame coding structure that facilitates periodic view switching and achieves an optimal tradeoff between storage cost and expected transmission rate. In this paper, we first propose three significant improvements over existing IMVS systems and then study the corresponding frame structure optimization. First, using depth-image-based rendering, the new IMVS system enables free viewpoint switching, i.e., by encoding and transmitting both texture and depth maps of captured views, a client can select and synthesize any virtual view from an almost continuum of viewpoints between the left-most and right-most captured views. Second, the IMVS system adopts a more realistic Markovian view-switching model with memory that more accurately captures user behaviors than previous memoryless models . A view-switching model is used in predicting client's future view-switching patterns. Third, assuming that the round-trip-time (RTT) delay during server–client communication is nonnegligible, during an IMVS session, the IMVS system additionally transmits redundant frames RTT into future playback, so that zero-delay view switching can be achieved. Given these improvements, we formalize a new joint optimization of the frame coding structure, transmission schedule, and quantization parameters of the texture and depth maps of multiple camera views. We propose an iterative algorithm to achieve fast and near-optimal solutions. The convergence of the algorithm is also demonstrated. Experimental results show that the proposed optimized rate-allocation method requires 38% lower transmission rate than the fixed rate-allocation scheme. In a- dition, with the same storage, the transmission rate of the optimized frame structure can be up to 55% lower than that of an I-frame-only structure and 27% lower than that of the structure without distributed source coding frames.
机译：在交互式多视图视频流（IMVS）中，客户端会接收并观察同一场景的许多可用视点之一，并会定期从服务器视图向相邻视图切换请求，因为视频会不间断地及时播放。一个关键的技术挑战是设计一种帧编码结构，该结构便于进行定期视图切换并在存储成本和预期传输速率之间实现最佳折衷。在本文中，我们首先提出对现有IMVS系统的三项重大改进，然后研究相应的帧结构优化。首先，使用基于深度图像的渲染，新的IMVS系统实现了自由的视点切换，即，通过编码和传输捕获视图的纹理图和深度图，客户端可以从几乎连续的视点之间选择并合成任何虚拟视图。最左侧和最右侧捕获的视图。其次，IMVS系统采用了更现实的带记忆的马尔可夫视图切换模型，比以前的无记忆模型更准确地捕获了用户行为。视图切换模型用于预测客户将来的视图切换模式。第三，假设服务器-客户端通信期间的往返时间（RTT）延迟不可忽略，则在IMVS会话期间，IMVS系统还会将冗余帧RTT传输到将来的回放中，从而可以实现零延迟视图切换。有了这些改进，我们就可以对多个摄像机视图的纹理和深度图的帧编码结构，传输计划以及量化参数进行新的联合优化。我们提出了一种迭代算法来实现快速且接近最优的解决方案。还证明了该算法的收敛性。实验结果表明，所提出的优化速率分配方法比固定速率分配方案所需的传输速率低38％。另外，在具有相同存储空间的情况下，优化帧结构的传输速率可以比仅I帧结构的传输速率低55％，比没有分布式源编码帧的结构的传输速率低27％。

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