Distributed multi-hypothesis coding of depth maps using texture motion information and optical flow

Matteo Salmistraro, M. Zamarin, L. L. Rakêt, Søren Forchhammer
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引用次数: 13

Abstract

Distributed Video Coding (DVC) is a video coding paradigm allowing a shift of complexity from the encoder to the decoder. Depth maps are images enabling the calculation of the distance of an object from the camera, which can be used in multiview coding in order to generate virtual views, but also in single view coding for motion detection or image segmentation. In this work, we address the problem of depth map video DVC encoding in a single-view scenario. We exploit the motion of the corresponding texture video which is highly correlated with the depth maps. In order to extract the motion information, a block-based and an optical flow-based methods are employed. Finally we fuse the proposed Side Informations using a multi-hypothesis DVC decoder, which allows us to exploit the strengths of all the proposed methods at the same time.
基于纹理运动信息和光流的深度图分布式多假设编码
分布式视频编码(DVC)是一种视频编码范式,允许从编码器到解码器的复杂性转移。深度图是能够计算物体与相机距离的图像,它可以用于多视图编码以生成虚拟视图,也可以用于运动检测或图像分割的单视图编码。在这项工作中,我们解决了单视图场景下深度图视频DVC编码的问题。我们利用了与深度图高度相关的相应纹理视频的运动。为了提取运动信息,采用了基于分块和光流的方法。最后,我们使用多假设DVC解码器融合提出的边信息,这使我们能够同时利用所有提出的方法的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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