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镜头边界检测的方法与挑战:综述

Methods and Challenges in Shot Boundary Detection: A Review.

作者信息

Abdulhussain Sadiq H, Ramli Abd Rahman, Saripan M Iqbal, Mahmmod Basheera M, Al-Haddad Syed Abdul Rahman, Jassim Wissam A

机构信息

Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia.

Department of Computer Engineering, University of Baghdad, Al-Jadriya 10071, Baghdad, Iraq.

出版信息

Entropy (Basel). 2018 Mar 23;20(4):214. doi: 10.3390/e20040214.

Abstract

The recent increase in the number of videos available in cyberspace is due to the availability of multimedia devices, highly developed communication technologies, and low-cost storage devices. These videos are simply stored in databases through text annotation. Content-based video browsing and retrieval are inefficient due to the method used to store videos in databases. Video databases are large in size and contain voluminous information, and these characteristics emphasize the need for automated video structure analyses. Shot boundary detection (SBD) is considered a substantial process of video browsing and retrieval. SBD aims to detect transition and their boundaries between consecutive shots; hence, shots with rich information are used in the content-based video indexing and retrieval. This paper presents a review of an extensive set for SBD approaches and their development. The advantages and disadvantages of each approach are comprehensively explored. The developed algorithms are discussed, and challenges and recommendations are presented.

摘要

网络空间中可用视频数量最近的增加归因于多媒体设备的可用性、高度发达的通信技术以及低成本存储设备。这些视频仅通过文本注释存储在数据库中。由于在数据库中存储视频所采用的方法,基于内容的视频浏览和检索效率低下。视频数据库规模庞大且包含大量信息,这些特性凸显了自动视频结构分析的必要性。镜头边界检测(SBD)被视为视频浏览和检索的一个重要过程。SBD旨在检测连续镜头之间的过渡及其边界;因此,具有丰富信息的镜头被用于基于内容的视频索引和检索。本文对一系列广泛的SBD方法及其发展进行了综述。全面探讨了每种方法的优缺点。讨论了已开发的算法,并提出了挑战和建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19a7/7512729/2ac8f0568cf8/entropy-20-00214-g001.jpg

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