DocumentCode :
1742979
Title :
Foreground-background segmentation by cellular neural networks
Author :
Giaccone, P.R. ; Tsaptsinos, D. ; Jones, G.A.
Author_Institution :
Kingston Univ., UK
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
438
Abstract :
A common procedure in digital postproduction is rotoscoping, the segmentation of independently moving foreground elements from background in a sequence of images. Still often carried our manually, rotoscoping is time-consuming and requires great skill in determining the boundary between foreground and background. Errors lead to a bubbling artefact in the final composited sequence. The industry is interested in automated rotoscoping. Any automatic segmentation method must correctly locate the boundary and be robust given rapid motion and non-static backgrounds. A cellular neural network for segmentation is presented that labels pixels by colour, estimated motion and neighbouring labels. The method is accurate, labour saving and many times faster than manual rotoscoping
Keywords :
cellular neural nets; image segmentation; motion estimation; bubbling artefact; digital postproduction; foreground-background segmentation; rotoscoping; Cellular neural networks; Computer science; Design for disassembly; Image segmentation; Labeling; Motion compensation; Motion estimation; Pixel; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.906106
Filename :
906106
Link To Document :
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