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Fast Disparity and Motion Estimation for Multi-view Video Coding

机译:多视点视频编码的快速视差和运动估计

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摘要

In this paper, we propose a fast disparity and motion estimation for multi-view video coding (MVC). When implementing MVC, one of the most critical problems is heavy computational complexity caused by the large amount of information in multi-view sequences. Hence, a fast algorithm is essential. To reduce this computational complexity, we adoptively controlled a search range considering the reliability of each macroblock. In order to estimate this reliability, we calculated the difference between the predicted vectors that were obtained from different methods. When working with conventional encoders, vectors can be predicted using median filtering from causal blocks. Moreover, we calculated another predicted vector using multi-view camera geometry or the relationship between the disparity and motion vectors. We assumed that this difference indicated the reliability of the current macroblock. By using these properties, we were able to determine new search range and reduce the number of searching points within the limited window. The proposed MVC system was tested with several multi- view sequences to evaluate performance. Experimental results showed that the proposed algorithm was able to reduce processing time by maximumly 70-80% in estimation process.
机译:在本文中,我们提出了一种用于多视图视频编码(MVC)的快速视差和运动估计。在实施MVC时,最关键的问题之一是由多视图序列中的大量信息引起的繁重的计算复杂性。因此,快速算法至关重要。为了减少这种计算复杂性,我们考虑到每个宏块的可靠性来过继地控制搜索范围。为了估计此可靠性,我们计算了从不同方法获得的预测向量之间的差异。当使用常规编码器时,可以使用因果块的中值滤波来预测矢量。此外,我们使用多视图相机几何形状或视差与运动矢量之间的关系计算了另一个预测矢量。我们假设这种差异表明了当前宏块的可靠性。通过使用这些属性,我们能够确定新的搜索范围并减少有限窗口内的搜索点数量。所提出的MVC系统已通过多个多视图序列进行了测试,以评估性能。实验结果表明,该算法在估计过程中最多可减少70-80%的处理时间。

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