Semantic-Based Video Retrieval Survey  

作　　者：Shaimaa Toriah Mohamed Toriah Atef Zaki Ghalwash Aliaa A. A. Youssif 

机构地区：[1]Department of Computer Science, Faculty of Computers and Informatics, Benha University, Benha, Egypt [2]Computer Science Department, Faculty of Computers and Information, Helwan University, Helwan, Egypt

出　　处：《Journal of Computer and Communications》2018年第8期28-44,共17页电脑和通信（英文）

摘　　要：There is a tremendous growth of digital data due to the stunning progress of digital devices which facilitates capturing them. Digital data include image, text, and video. Video represents a rich source of information. Thus, there is an urgent need to retrieve, organize, and automate videos. Video retrieval is a vital process in multimedia applications such as video search engines, digital museums, and video-on-demand broadcasting. In this paper, the different approaches of video retrieval are outlined and briefly categorized. Moreover, the different methods that bridge the semantic gap in video retrieval are discussed in more details.There is a tremendous growth of digital data due to the stunning progress of digital devices which facilitates capturing them. Digital data include image, text, and video. Video represents a rich source of information. Thus, there is an urgent need to retrieve, organize, and automate videos. Video retrieval is a vital process in multimedia applications such as video search engines, digital museums, and video-on-demand broadcasting. In this paper, the different approaches of video retrieval are outlined and briefly categorized. Moreover, the different methods that bridge the semantic gap in video retrieval are discussed in more details.

关 键 词：SEMANTIC Video RETRIEVAL CONCEPT Detectors CONTEXT Based CONCEPT FUSION SEMANTIC GAP 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]