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Semantic model vectors for complex video event recognition

Date

Authors

Merler, Michele

Huang, Bert

Xie, Lexing

Hua, Gang

Natsev, Apostol

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

We propose semantic model vectors, an intermediate level semantic representation, as a basis for modeling and detecting complex events in unconstrained real-world videos, such as those from YouTube. The semantic model vectors are extracted using a set of

Keywords

Keywords: Clip level; Descriptors; Empirical studies; Event detection; Event recognition; Feature fusion; Intermediate level; Semantic Model; Semantic representation; Spatio-temporal; Static features; SVM model; TRECVID; Video events; Web images; YouTube; Image ret Complex video events; event recognition; high-level descriptor

URI

http://hdl.handle.net/1885/67462

Collections

ANU Research Publications

Source

IEEE Transactions on Multimedia

Type

Journal article

DOI

10.1109/TMM.2011.2168948

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