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Adaptive Selection of Motion Models for Panoramic Video Coding

机译:全景视频编码运动模型的自适应选择

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A panoramic video is an image-based rendering (IBR) technique which provides users with a large field of view (e.g. 360 degree) on surrounding dynamic scenes. It includes not only the translational motions but also the non-translational motions, such as zooming, rotation and uneven stretching etc. This paper presents a motion compensated prediction scheme based on adaptive selection of motion models to predict the complex changes between successive frames efficiently in panoramic video coding. By performing the initial motion estimation phrase and the refined motion estimation phrase in the proposed scheme, simulated results show that the coding performance of the proposed scheme is much higher than the traditional motion compensated prediction scheme in panoramic video coding.
机译:全景视频是一种基于图像的渲染(IBR)技术,可为用户提供周围动态场景的大视野(例如360度)。它不仅包括平移运动,还包括非平移运动,例如缩放,旋转和不均匀拉伸等。本文提出了一种基于运动模型自适应选择的运动补偿预测方案,可以有效地预测连续帧之间的复杂变化。全景视频编码。通过对提出的方案进行初始运动估计短语和精细运动估计短语的仿真,仿真结果表明,该方案的编码性能比全景视频编码中的传统运动补偿预测方案高得多。

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