一种低延迟多视点视频加深度传输的自适应纹理深度率分配估计技术

M. Cordina, C. J. Debono
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引用次数: 1

摘要

本文提出了一种基于多元回归模型的低延迟多视点视频加深度传输的自适应纹理深度目标比特率分配估计技术。该技术利用深度图视频不连续区域宏块的预测模式分布,在考虑总可用比特率的情况下估计最优纹理-深度目标比特率分配。该方法在不同的标准测试序列中进行了测试,结果表明,该模型能够实时估计最佳纹理-深度率分配,绝对平均估计误差为2.5%,标准差为2.2%。此外,它允许纹理深度率分配适应视频序列具有良好的跟踪性能,允许正确处理场景的变化。
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An adaptive texture-depth rate allocation estimation technique for low latency multi-view video plus depth transmission
This paper presents an adaptive texture-depth target bit rate allocation estimation technique for low latency multi-view video plus depth transmission using a multi-regression model. The proposed technique employs the prediction mode distribution of the macroblocks at the discontinuity regions of the depth map video to estimate the optimal texture-depth target bit rate allocation considering the total available bit rate. This technique was tested using various standard test sequences and has shown efficacy as the model is able to estimate, in real-time, the optimal texture-depth rate allocation with an absolute mean estimation error of 2.5% and a standard deviation of 2.2%. Moreover, it allows the texture-depth rate allocation to be adapted to the video sequence with good tracking performance, allowing the correct handling of scene changes.
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