A new video indexing and retrieval method for temporal textures using block-based cooccurrence statistics

Author

Rahman, Ashfaqur ; Murshed, Manzur ; Dooley, Laurence S.

Author_Institution

Gippsland Sch. of Comp. & IT, Monash Univ., Churchill, Vic., Australia

fYear

2004

fDate

11-13 June 2004

Firstpage

136

Lastpage

139

Abstract

A new unified video indexing and retrieval method is presented to classify temporal texture videos using spatial as well as temporal cooccurrence statistics of block-based motion vectors, so keeping the computational complexity for retrieval within a real-time bound. Experimental results clearly demonstrate the superiority of the proposed method over existing temporal cooccurrence matrix-based solutions.

Keywords

computational complexity; image classification; image motion analysis; image retrieval; image sequences; image texture; matrix algebra; video signal processing; block-based cooccurrence statistics; computational complexity; cooccurrence matrix; motion activity; motion vectors; spatial cooccurrence statistics; temporal cooccurrence statistics; temporal textures; video indexing; video retrieval; video sequences; Australia; Computational complexity; Computer vision; Feature extraction; Focusing; Image segmentation; Indexing; Information retrieval; Statistics; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking and Communication Conference, 2004. INCC 2004. International

Print_ISBN

0-7803-8325-7

Type

conf

DOI

10.1109/INCC.2004.1366593

Filename

1366593