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Rate-complexity tradeoff for client-side free viewpoint image rendering

机译:客户端自由视点图像渲染的速率复杂度折衷

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Free viewpoint video enables a client to interactively choose a viewpoint from which to synthesize an image via depth-image-based rendering (DIBR). However, synthesizing a novel viewpoint image using texture and depth maps from two nearby views entails a sizable computation overhead. Further, to reduce transmission rate, recent proposals synthesize the second reference view itself using texture and depth maps of the first reference view via a complex inpainting algorithm to complete large disocclusion holes in the second reference image-a small amount of auxiliary information (AI) is transmitted by sender to aid the inpainting process-resulting in an even higher computation cost. In this paper, we study the optimal tradeoff between transmission rate and client-side complexity, so that in the event that a client device is computation-constrained, complexity of DIBR-based view synthesis can be scalably reduced at the expense of a controlled increase in transmission rate. Specifically, for standard view synthesis paradigm that requires texture and depth maps of two neighboring reference views, we design a dynamic programming algorithm to select the optimal subset of intermediate virtual views for rendering and encoding at server, so that a client performs only video decoding of these views, reducing overall view synthesis complexity. For new view synthesis paradigm that synthesizes the second reference view itself from the first, we optimize the transmission of AI used to assist inpainting of large disocclusion holes, so that some computation-expensive exemplar block search operations are avoided, reducing inpainting complexity. Experimental results show that the proposed schemes can scalably and gracefully reduce client-side complexity, and the proposed optimizations achieve better rate-complexity tradeoff than competing schemes.
机译:免费的视点视频使客户能够通过基于深度图像的渲染(DIBR)交互地选择视点来合成图像。然而,使用来自两个附近视图的纹理和深度图来合成新颖的视点图像需要大量的计算开销。此外,为了降低传输速率,最近的提议是通过复杂的修复算法使用第一参考视图的纹理和深度图来合成第二参考视图本身,以完成第二参考图像中的大遮挡孔-少量辅助信息(AI)由发送方发送以帮助修复过程,从而导致更高的计算成本。在本文中,我们研究了传输速率与客户端复杂度之间的最佳折衷,以便在客户端设备受到计算限制的情况下,可以以可控的增加为代价来逐步降低基于DIBR的视图合成的复杂性在传输速率上。具体来说,对于需要两个相邻参考视图的纹理和深度图的标准视图合成范式,我们设计了一种动态编程算法,以选择中间虚拟视图的最佳子集以在服务器上进行渲染和编码,以便客户端仅对视频进行解码。这些视图,降低了整体视图综合的复杂性。对于从第一个参考视图本身合成第二个参考视图的新视图合成范例,我们优化了用于辅助大遮挡孔修复的AI传输,从而避免了一些计算量大的示例块搜索操作,从而降低了修复复杂性。实验结果表明,所提出的方案可以规模化,优雅地降低客户端的复杂度,并且所提出的优化方案比竞争方案具有更好的速率复杂度折衷。

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