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A parallel true motion estimation method based on binarized cross correlation

机译：基于二值化互相关的并行真实运动估计方法

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Block based recursive search for motion estimation is already suitable for real time applications thanks to its wide utilization, but the increase of resolution in modern displays and the need for real time software implementations demand for faster approaches. In this paper a new motion estimation procedure that has been developed for a parallel implementation is presented. The parallel implementation was achieved by avoiding the spatial recursion which is typical for the recursive search systems, while the convergence can still be obtained by means of the temporal recursion only. In particular the use of a binarized cross correlation as a matching cost criteria instead of the standard SAD permits an improved motion vector field and a faster convergence without increasing the computational cost. The experimental results show a similar vector field estimation in comparison to the standard SAD based recursive search method with the considerable advantage of a possible parallel implementation.
机译：由于其广泛的应用，基于块的递归搜索运动估计已经适合于实时应用，但是现代显示器中分辨率的提高以及对实时软件实现的需求要求采用更快的方法。在本文中，提出了一种为并行实现而开发的新运动估计程序。并行实现是通过避免空间递归来实现的，而空间递归对于递归搜索系统来说是典型的，而收敛仍然只能通过时间递归来获得。特别地，使用二值化互相关作为匹配成本标准而不是标准SAD允许在不增加计算成本的情况下改善运动矢量场和更快收敛。实验结果表明，与基于标准SAD的递归搜索方法相比，矢量场估计相似，并且具有可能的并行实现的显着优势。

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