摘要
随着互联网和数字技术的快速发展,视频数据在网络中的重要性日益凸显,用户对视频检索的需求随之增加。针对传统视频检索方法在挖掘视频内容方面的局限性,设计一种融合多模态信息的电视视频检索系统,利用深度学习技术从视频中提取图像和文本信息,并建立检索模型以进行信息融合,最后为融合后的信息建立储存服务器,实现更准确、更全面的视频检索。
With the rapid development of internet and digital technology,the importance of video data in the network has become increasingly prominent,and users'demand for video retrieval has increased.In view of the limitations of traditional video retrieval methods in mining video content,this paper designs a television video retrieval system that integrates multi-modal information,uses deep learning technology to extract image and text information from video,and establishes a retrieval model for information fusion,and finally establishes a storage server for the fused information to achieve more accurate and comprehensive video retrieval.
作者
张玉艳
ZHANG Yuyan(Shandong Rizhao Radio and Television Station,Rizhao 276800,China)
出处
《电视技术》
2024年第4期40-42,共3页
Video Engineering
关键词
多模态信息
电视视频
检索系统
multimodal information
television video
retrieval system