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A VIDEO OBJECT SEGMENTATION SCHEME TO LOWER COMPLEXITY IN MULTI-VIEW VIDEO CODING

机译:在多视图视频编码中降低复杂度的视频对象分割方案

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Exploiting redundancy is the hallmark of traditional video coding but is even more essential in multi-view video coding (MVC). The exploitation of additional redundancies, however, incurs extra computational complexity, counteracting the benefits gained from coding efficiency. In this paper, we propose an efficient segmentation scheme for MVC, which aims to lower complexity while achieving high coding efficiency in MVC. The proposed scheme is applied to the base view in MVC using the intensity of decoded frames and motion vectors of base view, which can be also recovered by the decoder. Therefore, no segmentation masks need to be encoded. So that increase of complexity and output bit rate from segmentation can be limited, allowing fast and on-line processing. The segmented objects in base view are then applied to an object-based MVC, which using object registration and warping to predict enhancement views (EVs) and initial disparity maps of EVs. These features are utilized in lowering the complexity of EVs' coding. The experimental results show that the proposed technique provides high quality and consistent segmentation masks with low computational complexity. In addition, by applying the proposed scheme, high coding efficiency and low complexity object-based MVC is achieved.
机译:利用冗余是传统视频编码的标志,但在多视图视频编码(MVC)中则更为重要。但是,利用额外的冗余会导致额外的计算复杂性,从而抵消了编码效率带来的好处。在本文中,我们提出了一种有效的MVC分割方案,旨在降低复杂度,同时在MVC中实现较高的编码效率。所提出的方案利用解码后的帧的强度和基本视图的运动矢量将其应用于MVC中的基本视图,该解码器也可以恢复该强度。因此,不需要对分割掩码进行编码。因此,可以限制复杂性和分段输出比特率的增加,从而实现快速在线处理。然后,将基本视图中的分段对象应用于基于对象的MVC,后者使用对象注册和变形来预测增强视图(EV)和EV的初始视差图。这些功能可用于降低EV编码的复杂性。实验结果表明,所提出的技术提供了高质量和一致的分割蒙版,且计算复杂度较低。另外,通过应用所提出的方案,实现了高编码效率和低复杂度的基于对象的MVC。

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