DocumentCode :
3451855
Title :
Interactive video GrowCut: A semi-automated video object segmentation framework using cellular automata
Author :
Phan, Raphael ; Androutsos, D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
fYear :
2011
fDate :
8-11 May 2011
Abstract :
This paper illustrates a simple, yet effective semi-automated object segmentation framework over video sequences. This is through an extension of the GrowCut framework, an image segmentation scheme based on cellular automata. We describe how GrowCut is extended to video sequences, as well as providing our own improvements and addressing problematic areas to the original formulation. This provides a good increase in accuracy and creates the main goal of this work. It will be shown that the original algorithm adapts quite nicely to video object segmentation, and can achieve very good results using both synthetic and real video footage, obtained from different sources.
Keywords :
cellular automata; image segmentation; image sequences; interactive video; video signal processing; cellular automata; image segmentation scheme; interactive video GrowCut; real video footage; semiautomated video object segmentation; synthetic video footage; video sequence; Accuracy; Automata; Force; Image color analysis; Image segmentation; Object segmentation; Video sequences; Cellular Automata; Computer Vision; GrowCut; Image & Video Processing; Video Object Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference on
Conference_Location :
Niagara Falls, ON
ISSN :
0840-7789
Print_ISBN :
978-1-4244-9788-1
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2011.6030413
Filename :
6030413
Link To Document :
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