DocumentCode :
432931
Title :
Real-time temporal texture characterisation using block-based motion co-occurrence statistics
Author :
Rahman, Ashfaqur ; Murshed, Munzitr
Author_Institution :
Gippsland Sch. of Comp. & IT, Monash Univ., Churchill, Vic., Australia
Volume :
3
fYear :
2004
fDate :
24-27 Oct. 2004
Firstpage :
1593
Abstract :
Contemporary temporal texture classification methods use pixel based features thus making the process slow for time sensitive applications like video indexing and surveillance. In this paper, a real-time classification technique is presented by using readily available block based motion vectors. Experimental results demonstrate the ability of the proposed technique to classify a large set of temporal textures in real-time with high accuracy.
Keywords :
image classification; image motion analysis; image sequences; image texture; indexing; statistical analysis; surveillance; video signal processing; block-based motion co-occurrence statistics; image sequence; motion vector; real-time temporal texture characterisation; texture classification method; video indexing; video surveillance; Australia; Feature extraction; Fluid flow measurement; Image sequences; Indexing; Motion measurement; Pixel; Spatiotemporal phenomena; Statistical distributions; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-8554-3
Type :
conf
DOI :
10.1109/ICIP.2004.1421372
Filename :
1421372
Link To Document :
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