基于深度图像分层分离(DILS)算法的多相机视角系统多层次视角合成(MLVS

N. A. Manap, J. Soraghan, L. Petropoulakis
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引用次数: 0

摘要

提出了一种新的多视角合成(MLVS)方法,用于三维视觉和自由视点视频应用,如光场成像。MLVS利用深度图像层分离(deep Image Layer Separation, DILS)的优势,将立体图像扩展到多摄像机配置。该技术通过两个层次的匹配和合成过程来寻找像素对应点并进行合成。MLVS的主要目的是通过减少实际图像采集相机的数量来创建一个多相机视图系统,同时保持虚拟视图合成图像的质量。与传统的大容量摄像机配置相比,所提出的技术被证明可以提供更好的性能,并提供更多的视角,用于自由视点视频采集。因此,可以在处理、校准、带宽和存储要求方面节省大量成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Level View Synthesis (MLVS) based on Depth Image Layer Separation (DILS) algorithm for multi-camera view system
A novel Multi-Level View Synthesis (MLVS) approach for 3D vision and free-viewpoint video applications, such as light field imaging, is presented. MLVS exploits the advantages of Depth Image Layer Separation (DILS), a new inter-view interpolation algorithm, by extending stereo to multiple camera configurations. The technique finds the pixel correspondences and synthesis through two levels of matching and synthesis process. The main aim of MLVS is to create a multi-camera view system through a reduced number of actual image acquisition cameras, whilst maintaining the quality of the virtual view synthesis images. The proposed technique is shown to offer improved performance and provide additional views with fewer cameras compared to conventional high volume camera configurations for free-viewpoint video acquisition. Thus, substantial cost savings can ensue in processing, calibration, bandwidth and storage requirements.
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