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Recursive Video Matting and Denoising

机译:递归视频抠图和去噪

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摘要

In this paper, we propose a video matting method with simultaneous noise reduction based on the Unscented Kalman filter (UKF). This recursive approach extracts the alpha mattes and denoised foregrounds from noisy videos, in a unified framework. No assumptions are made about the type of motion of the camera or of the foreground object in the video. Moreover, user-specified trimaps are required only once every ten frames. In order to accurately extract information at the borders between the foreground and the background, we include a discontinuity-adaptive Markov random field (MRF) prior. It incorporates spatio-temporal information from the current and previous frame during estimation of the alpha matte as well as the foreground. Results are given on videos with real film-grain noise.
机译:在本文中,我们提出了一种基于无味卡尔曼滤波器(UKF)同时降噪的视频消光方法。这种递归方法在统一的框架中从嘈杂的视频中提取出Alpha遮罩和去噪的前景。不对摄像机或视频中前景对象的运动类型做出任何假设。而且,用户指定的三映射仅需每十帧一次。为了准确地提取前景和背景之间的边界处的信息,我们在前面包含了不连续性的马尔可夫随机场(MRF)。它在估计alpha遮罩以及前景时合并了当前帧和前一帧的时空信息。在具有真实胶片颗粒噪声的视频上给出了结果。

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