基于视频的机器人学习方法

Yuantao Tang
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引用次数: 0

摘要

随着5G时代的到来,以及计算机技术和数字视频技术的不断发展,视频数据量日益增加。因此,在现实生活中存在着能够在保留原视频主要内容的前提下大幅缩短视频时长的技术要求。视频摘要方法的出现很好地满足了这一需求。它可以减少人们浏览视频的时间,同时节省大量的存储空间。视频摘要是从视频中自动提取关键信息并以摘要的形式呈现的过程。它已经被证明对人类和机器都很有用,因为它可以帮助他们在不看整个视频的情况下理解视频的主要思想。在本文中,我们将专注于使用深度学习技术进行视频摘要。深度学习是一项有效的技术,因为它可以通过分析数据样本来学习复杂的函数。这也使它成为一种理想的总结技术,因为视频包含了大量所需的信息。本文研究了各种类型的视频,提出了一种基于视频摘要的机器人学习方法,以提高视频摘要算法的性能,生成用户感兴趣的视频摘要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robot Learning Method Based On Video
With the arrival of 5G era and the continuous development of computer technology and digital video technology, the amount of video data is increasing day by day. Therefore, there is a technical requirement in real life that can significantly shorten the video duration while retaining the main content of the original video. The emergence of video summarization method successfully meets this demand. It can reduce the time for people to browse videos and save a lot of storage space at the same time. Video summary is the process of automatically extracting key information from video and presenting it in the form of summary. It has been proved to be useful for both humans and machines because it can help them understand the main idea of video without watching the whole video. In this paper, we will focus on using deep learning technology for video summarization. Deep learning is an effective technology for many tasks, because it can learn complex functions by analyzing data samples. This also makes it an ideal summary technology, because video contains a lot of information needed. This paper studies various types of video, and proposes a robot learning method based on video summarization to improve the performance of video summarization algorithm and generate video summaries that interest users.
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