高效的关键帧提取和视频分析

J. Calic, E. Izquierdo
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引用次数: 100

摘要

基于内容的视频索引与检索的基础是对主要视频时间结构的分析。因此,视频分割和关键帧提取技术对先进数字视频系统的发展至关重要。传统的视频分割和关键帧提取算法主要是自主实现的。通过对压缩视频特征的分析,本文介绍了一种实时场景变化检测和关键帧提取算法,该算法通过分析从MPEG压缩流中提取的宏块特征的统计量来生成帧差度量。关键帧提取方法采用离散轮廓进化算法,利用曲线化简中的差分度量实现。这种方法产生了一种快速且鲁棒的算法。报告了计算机模拟的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient key-frame extraction and video analysis
Content-based video indexing and retrieval has its foundations in the analyses of the prime video temporal structures. Consequently, technologies for video segmentation and key-frame extraction have become crucial for the development of advanced digital video systems. Conventional algorithms for video partitioning and key-frame extraction are mainly implemented autonomously. By focusing the analysis on compressed video features, this paper introduces a real-time algorithm for scene change detection and key-frame extraction that generates frame difference metrics by analysing the statistics of the macro-block features extracted from an MPEG compressed stream. The key-frame extraction method is implemented using difference metrics in curve simplification by means of a discrete contour evolution algorithm. This approach resulted in a fast and robust algorithm. Results of computer simulations are reported.
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