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Yet Another Fast and Robust Feature-based Motion Estimation and Background Layer Extraction

机译:另一个基于特征的快速而稳健的运动估计和背景层提取

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摘要

In this paper, we describe a method for estimating and stabilizing a dominant motion between two images by 2D pair-wise image registration. Pair-wise image registration estimates 2D transformation parameters between consecutive frames. The transformation between non-consecutive frames is computed by the concatenation of the pair-wise transformations. This pair-wise registration is based on 1) hierarchical parameter estimation and refinement 2) feature-matching 3) FFT-based global matching 4) RANSAC-based parameter estimation. After motion estimation and stabilization, we extract staticon-static components of the video stream and represent them as background/foreground layers. The layer extraction is based on color distribution and netflow analysis. The extracted layers provide a basis for a compact description of a video. The presented approach is illustrated by a set of challenging examples.
机译:在本文中,我们描述了一种通过二维成对图像配准来估计和稳定两个图像之间的主导运动的方法。逐对图像配准估计连续帧之间的2D转换参数。非连续帧之间的转换是通过逐对转换的级联来计算的。这种成对注册基于1)层次参数估计和细化2)特征匹配3)基于FFT的全局匹配4)基于RANSAC的参数估计。经过运动估计和稳定后,我们提取视频流的静态/非静态分量,并将其表示为背景/前景层。图层提取基于颜色分布和净流分析。提取的层为视频的紧凑描述提供了基础。一组具有挑战性的示例说明了所提出的方法。

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