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Adaptive Subspace Symbolization for Content-Based Video Detection

Date

Authors

Zhou, Xiangmin

Zhou, Xiaofang

Chen, Lei

Shu, Yangeng

Bouguettaya, Athman

Taylor, John A.

Publisher

IEEE Computer Society

Abstract

Efficiently and effectively identifying similar videos is an important and nontrivial problem in content-based video retrieval. This paper proposes a subspace symbolization approach, namely SUDS, for content-based retrieval on very large video databases.

Keywords

Keywords: Adaptive approach; Adaptive subspaces; Compensation scheme; Content-based; Content-based video retrieval; Data distribution; Data simplification; Dominant subspace; Key-frames; Query optimization; Similarity measure; String matching; subspace symbolizatio query optimization.; subspace symbolization; variable length partition; Video detection

URI

http://hdl.handle.net/1885/55959

Collections

ANU Research Publications

Source

IEEE Transactions on Knowledge and Data Engineering

Type

Journal article

DOI

10.1109/TKDE.2009.171

Restricted until

2037-12-31

Downloads

File

Description

01_Zhou_Adaptive_Subspace_2010.pdf (2.3 MB)