A Survey on Visual Content-Based Video Indexing and Retrieval

被引：352

作者：

Hu, Weiming ^{[1
]}

Xie, Nianhua ^{[1
]}

Li, Li ^{[1
]}

Zeng, Xianglin ^{[1
]}

Maybank, Stephen ^{[2
]}

机构：

[1] Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China

[2] Univ London Birkbeck Coll, Dept Comp Sci & Informat Syst, London WC1E 7HX, England

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS | 2011年 / 41卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Feature extraction; video annotation; video browsing; video retrieval; video structure analysis; SHOT-BOUNDARY DETECTION; KEY-FRAME-EXTRACTION; MULTIMEDIA INFORMATION-RETRIEVAL; OF-THE-ART; UNIFIED FRAMEWORK; COMPRESSED VIDEO; CONCEPT ONTOLOGY; SCENE DETECTION; EVENT DETECTION; SOCCER VIDEO;

D O I：

10.1109/TSMCC.2011.2109710

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Video indexing and retrieval have a wide spectrum of promising applications, motivating the interest of researchers worldwide. This paper offers a tutorial and an overview of the landscape of general strategies in visual content-based video indexing and retrieval, focusing on methods for video structure analysis, including shot boundary detection, key frame extraction and scene segmentation, extraction of features including static key frame features, object features and motion features, video data mining, video annotation, video retrieval including query interfaces, similarity measure and relevance feedback, and video browsing. Finally, we analyze future research directions.

引用

页码：797 / 819

页数：23

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