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A robust method for camera motion estimation in movies based on optical flow

机译:一种基于光流的电影中摄像机运动估计的鲁棒方法

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摘要

Camera motion estimation plays an important role in digital video analysis algorithms such as video indexing and retrieval or automatic movie analysis. Several algorithms have been proposed to solve this problem in MPEG videos. This paper presents an optical flow-based approach for the camera motion estimation in all kinds of digital video formats, especially in movies. It compares the motion vector fields (MVFs) with six predefined templates to determine the type of motion. The MVFs are generated by using high-accuracy optical flow computation. The advantage of the method lies in its robustness to noisy environments such as false motion vectors and object motions. Comprehensive experiments with video clips extracted from well-known feature movies demonstrate the performance of the proposed approach.
机译:摄像机运动估计在数字视频分析算法(例如视频索引和检索或自动电影分析)中扮演着重要角色。已经提出了几种算法来解决MPEG视频中的这个问题。本文提出了一种基于光流的方法,用于各种数字视频格式(尤其是电影)中的摄像机运动估计。它将运动矢量字段(MVF)与六个预定义的模板进行比较,以确定运动的类型。 MVF是通过使用高精度光流计算生成的。该方法的优点在于其对诸如假运动矢量和物体运动之类的嘈杂环境的鲁棒性。对从著名故事片中提取的视频片段进行的综合实验证明了该方法的性能。

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