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A motion vector prediction method for multi-view video coding

机译:用于多视点视频编码的运动矢量预测方法

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This paper proposes a new motion vector (MV) prediction method in multi-view video coding (MVC). In order to exploit the information in adjacent views, inter-view MVs as well as temporal MVs are used in conventional MVC. Since the inter-view MVs are usually uncorrelated with the temporal MVs and most neighboring partitions have temporal MVs only, the conventional DPCM coding gain of inter-view MV is very low and thus the inter-view MVs are seldom selected. In order to increase the probability of interview MV selection, we define a virtual inter-view MV which can be generated from temporal MVs. Then, an inter-view MV is predicted using these neighboring virtual inter-view MVs, leading to less prediction error than using the temporal MVs. As a result, bit-rates are decreased by up to 9% for the view-temporal prediction structure.
机译:提出了一种多视点视频编码(MVC)中的运动矢量(MV)预测方法。为了利用相邻视图中的信息,在传统的MVC中使用视图间MV和时间MV。由于视图间MV通常与时间MV不相关,并且大多数相邻分区仅具有时间MV,因此视图间MV的传统DPCM编码增益非常低,因此很少选择视图间MV。为了增加采访MV选择的可能性,我们定义了可以从时间MV生成的虚拟视图间MV。然后,使用这些相邻的虚拟视图间MV来预测视图间MV,与使用时间MV相比,导致更少的预测误差。结果,对于视图时间预测结构,比特率最多降低了9%。

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