DocumentCode
1740397
Title
A high-level semantics extraction model for stored videos
Author
Liu, Yan ; Li, Fei
Author_Institution
Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear
2000
fDate
2000
Firstpage
71
Lastpage
74
Abstract
Digital video databases have become more pervasive, and finding video clips in video databases is quickly becoming a major bottleneck. Indexing and annotation can help video systems retrieve appropriate video clips fast. Currently, these techniques are based on computation on image low-level features and manual annotation, whose low success ratio and retrieval speed limit the applications of video databases. In this paper, we consider the semantic interpretation of the the contents as a form of annotation for video clips. We give a self-adaptive high-level description model for application-oriented semantics extraction, which annotates and retrieves video clips flexibly and automatically
Keywords
content-based retrieval; database indexing; video databases; annotation; application-oriented semantics extraction; digital video databases; high-level semantics extraction model; image low-level features; indexing; self-adaptive high-level description model; stored videos; video clip retrieval; Computer science; Content based retrieval; Data mining; Feature extraction; Image retrieval; Information retrieval; Layout; Prototypes; Spatial databases; Videos;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Software Engineering, 2000. Proceedings. International Symposium on
Conference_Location
Taipei
Print_ISBN
0-7695-0933-9
Type
conf
DOI
10.1109/MMSE.2000.897194
Filename
897194
Link To Document