DocumentCode
1740910
Title
Statistical feature extraction from compressed video sequences
Author
Fernando, W.A.C. ; Canagarajah, C.N. ; Bull, D.R.
Author_Institution
Centre for Commun. Res., Bristol Univ., UK
Volume
3
fYear
2000
fDate
2000
Firstpage
925
Abstract
To maximise the benefits from data compression, it would be advantageous to develop algorithms that do not require decompression to extract relevant information for post processing. In this paper, a novel technique for extracting variance is proposed for MPEG-2 compressed video using Parseval´s theorem. Results show that the estimated variance closely matches with the actual variance. Furthermore, this technique is applied to identify scene changes in the compressed domain
Keywords
data compression; feature extraction; image recognition; image sequences; statistical analysis; video coding; MPEG-2 compressed video; Parseval´s theorem; compressed domain; compressed video sequences; data compression; scene changes; statistical feature extraction; variance; Data compression; Data mining; Equations; Feature extraction; Image coding; Image storage; Layout; Transform coding; Video compression; Video sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location
Vancouver, BC
ISSN
1522-4880
Print_ISBN
0-7803-6297-7
Type
conf
DOI
10.1109/ICIP.2000.899608
Filename
899608
Link To Document