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
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;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899608
