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Temporally Consistent Depth Maps Recovery from Stereo Videos

机译:从立体声视频中临时一致的深度图恢复

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摘要

Dense depth maps provide significant geometry information for 3D video and free viewpoint video systems. Traditional stereo correspondence methods usually deal with each stereo image pair separately. As a result, the generated depth sequence is temporally inconsistent. This paper presented a novel approach to recover spatio-temporally consistent depth maps. The proposed method first applied sequential belief propagation algorithm to achieve an approximate minimum of spatial energy on Markov random fields. Then in temporal domain, a smoothness cost along optical flow was incorporated between consecutive frames. The combined cost which determined the disparity value was passed forward and temporal consistency was enforced during the process. In addition, the streamlined implementation was time and memory efficient. In experimental validation, quantitative evaluation as well as subject assessment was performed on several test datasets. The results showed that the proposed method yielded temporally consistent depth sequence and reduced flickering artifacts in the synthesized view while maintaining visual quality.
机译:密集的深度图为3D视频和自由视点视频系统提供了重要的几何信息。传统的立体对应方法通常会分别处理每个立体图像对。结果,所生成的深度序列在时间上是不一致的。本文提出了一种新颖的方法来恢复时空一致的深度图。所提出的方法首先应用顺序置信传播算法,以在马尔可夫随机场上获得空间能量的近似最小值。然后,在时域中,沿着光流的平滑度成本被合并在连续帧之间。决定差异值的合并成本被向前传递,并且在此过程中实施了时间一致性。此外,简化的实现节省了时间和内存。在实验验证中,对几个测试数据集进行了定量评估和主题评估。结果表明,所提出的方法在保持视觉质量的同时,在合成视图中产生了时间上一致的深度序列,并减少了闪烁现象。

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