视频超链接方法中的视觉描述符

P. Galuscáková, Michal Batko, Jan Cech, Jiri Matas, David Novak, Pavel Pecina
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引用次数: 2

摘要

在本文中,我们概述了不同的最新的视觉处理方法,并利用它们在超链接。视觉信息使用特征签名、明喻描述符和卷积神经网络(CNN)计算,作为视频帧之间的相似性,用于寻找相似的人脸、物体和环境。自动识别框架中的视觉概念,并将识别的文本输出与基于字幕和文本的搜索相结合。所有实验都在搜索和超链接2014年中世纪任务和视频超链接2015年TRECVid任务中进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual Descriptors in Methods for Video Hyperlinking
In this paper, we survey different state-of-the-art visual processing methods and utilize them in hyperlinking. Visual information, calculated using Features Signatures, SIMILE descriptors and convolutional neural networks (CNN), is utilized as similarity between video frames and used to find similar faces, objects and setting. Visual concepts in frames are also automatically recognized and textual output of the recognition is combined with search based on subtitles and transcripts. All presented experiments were performed in the Search and Hyperlinking 2014 MediaEval task and Video Hyperlinking 2015 TRECVid task.
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