Notice of Violation of IEEE Publication PrinciplesA Novel View Multi-view Synthesis Approach for Free Viewpoint Video

Yuhua Zhu
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Abstract

Interactive audio-visual applications such as free viewpoint video (FVV) endeavour to provide unrestricted spatiotemporal navigation within a multiple camera environment. Current novel view creation approaches for scene navigation within FVV applications are both purely image-based, implying large information redundancy and dense sampling of the scene; or involve reconstructing complex 3-D models of the scene. In this paper we present a new multiple image view synthesis algorithm for novel view creation that requires only implicit scene geometry information. The multi-view synthesis approach can be used in any multiple camera environments and is scalable, as virtual views can be created given 1 to N of the available video inputs, providing a means to gracefully handle scenarios where camera inputs decrease or increase over time. The algorithm identifies and selects only the best quality surface areas from available reference images, thereby reducing perceptual errors in virtual view reconstruction. Experimental results are provided and verified using both objective (PSNR) and subjective comparisons and also the improvements over the traditional multiple image view synthesis approach of view-oriented weighting are presented.
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一种新的自由视点视频多视点合成方法
交互式视听应用,如自由视点视频(FVV)努力在多摄像头环境中提供不受限制的时空导航。当前在FVV应用程序中,用于场景导航的新颖视图创建方法都是纯粹基于图像的,这意味着大量的信息冗余和密集的场景采样;或者重建复杂的场景三维模型。本文提出了一种新的多图像视图合成算法,该算法只需要隐式的场景几何信息。多视图合成方法可用于任何多摄像机环境,并且具有可扩展性,因为可以在给定1到N个可用视频输入的情况下创建虚拟视图,从而提供了一种优雅地处理摄像机输入随时间减少或增加的场景的方法。该算法从可用的参考图像中识别并选择质量最好的表面区域,从而减少虚拟视图重建中的感知误差。给出了实验结果,并通过客观(PSNR)和主观对比验证了实验结果,并对传统的多图像视图加权合成方法进行了改进。
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