DocumentCode :
2619163
Title :
Accurate silhouette segmentation using motion detection and graph cuts
Author :
Chen, Daniel ; Denman, Simon ; Fookes, Clinton
Author_Institution :
Image & Video Res. Lab., Queensland Univ. of Technol., Brisbane, QLD, Australia
fYear :
2010
fDate :
10-13 May 2010
Firstpage :
81
Lastpage :
84
Abstract :
Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.
Keywords :
graph theory; image segmentation; motion estimation; visual databases; ETISEO database; accurate silhouette segmentation; computer vision application; graph cuts; motion detection; robust segmentation; Back; Biomedical imaging; Image color analysis; Image edge detection; Image segmentation; Motion segmentation; Real time systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences Signal Processing and their Applications (ISSPA), 2010 10th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-7165-2
Type :
conf
DOI :
10.1109/ISSPA.2010.5605501
Filename :
5605501
Link To Document :
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