流媒体中依赖于场景上下文的关键帧选择

Anthony G. Nguyen, Jenq-Neng Hwang
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引用次数: 3

摘要

在本文中,我们描述了基于场景上下文的关键帧选择方法的发展,以减少录制的视频数据量。我们建议在关键帧选择过程中使用运动分析(MA)来适应场景内容。根据运动分析阶段产生的信息,选择视频序列中含有重要运动信息的帧进行记录。结果表明,该方法的性能优于传统的延时记录方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scene context dependent key frame selection in streaming
In this paper, we describe the development of our scene context dependent key frame selection method to reduce the amount of recorded video data. We propose the use of motion analysis (MA) to adapt to scene content in our key frame selection process. Based on the information generated by the motion analysis stage, frames in the video sequence which contain significant motion information are selected to retain for recording. We also show that our proposed method performs better than the traditional time-lapse recording method.
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