State-of-the-art on spatio-temporal information-based video retrieval

被引:30
|
作者
Ren, W. [2 ]
Singh, S. [1 ]
Singh, M. [1 ]
Zhu, Y. S. [2 ]
机构
[1] Univ Loughborough, Res Sch Informat, Loughborough LE11 3TU, Leics, England
[2] Peking Univ, Shenzhen Grad Sch, Key Lab Integrated Microsyst, Beijing, Peoples R China
基金
新加坡国家研究基金会;
关键词
Video retrieval; Semantic knowledge; Content-based analysis; Spatio-temporal information; SPATIAL KNOWLEDGE REPRESENTATION; SIMILARITY RETRIEVAL; RELEVANCE-FEEDBACK; IMAGE RETRIEVAL; MOTION; RECOGNITION; DESIGN; SHAPE; IMPLEMENTATION; OBJECTS;
D O I
10.1016/j.patcog.2008.08.033
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Video retrieval is increasingly based on image content. A number of studies on video retrieval have used low-level pixel content related to statistical moments, shape, colour and texture. However, it is well recognised that such information is not enough for uniquely discriminating across different multimedia content. The use of semantic information, especially which derived from spatio-temporal analysis is of great value in multimedia annotation, archiving and retrieval. In this review paper, we detail how the use of spatiotemporal semantic knowledge is changing the way in which modern research the conducted. In this paper we review a number of studies and concepts related to such analysis, and draw important conclusions on where future research is headed. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:267 / 282
页数:16
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