基于多模态信息融合的电视节目分割

Hongliang Bai, Lezi Wang, Gang Qin, Jiwei Zhang, Kun Tao, Xiaofu Chang, Yuan Dong
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引用次数: 5

摘要

提出了一种融合大规模视频中多模态信息的电视节目分割算法。由于“Inter-Programs”通常是在电视视频中反复插入,通过识别特殊序列的视频音频特征,可以有效地自动生成视频的宏观结构。电子节目指南(EPG)用于将结构组织到节目中。该算法包括三个部分,即基于视频的无监督重复序列检测、基于音频的特殊片段检索和基于epg的24小时节目分割。该算法已经在60天不同类型的电视视频中进行了测试。多模态融合和基于视频的重复序列检测的f值分别达到98%和96%以上。实验结果表明,该方法对电视节目分割具有较高的效率和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TV program segmentation using multi-modal information fusion
A TV program segmentation algorithm is presented by the fusion of the multi-modal information in the large-scale videos. As "Inter-Programs" are generally inserted into the TV videos repeatedly, the macro structures of the videos can be effectively and automatically generated by identifying the video-audio features of the special sequences. The Electronic Program Guide (EPG) is used to organize the structures into the programs. Three sections are included in the algorithm, namely, the video-based non-supervised duplicate sequence detection, the audio-based special clip retrieval and the EPG-based 24-hour program segmentation. The algorithm has been tested in 60-day different-type TV videos. The F-measures of the multi-modal fusion and video-based duplicated sequence detection achieve the rates of over 98% and 96% respectively. These results show that the proposed method is highly efficient and effective for the TV Program segmentation.
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