DocumentCode
456971
Title
A New Image Segmentation Method for Removing Background of Object Movies by Learning Shape Priors
Author
Ko, Cheng-Hung ; Tsai, Yu-Pao ; Shih, Zen-Chung ; Hung, Yi-Ping
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., National Taiwan Univ., Taipei
Volume
1
fYear
0
fDate
0-0 0
Firstpage
323
Lastpage
326
Abstract
This paper proposes a new object movie (OM) segmentation method that incorporates shape priors into the segmentation algorithm. The shape prior introduced into every image of the OM is learned from the 3D model reconstructed by the volumetric graph cuts. Here, the constraint derived from the discrete medial axis is used to improve the reconstruction algorithm. Our segmentation method requires only a small amount of user intervention, which is to select a subset of acceptable segmentations of the OM after the initial segmentation process. Compared to other techniques, our method provides not only the better segmentation result but also the better 3D reconstruction result
Keywords
feature extraction; graph theory; image reconstruction; image segmentation; stereo image processing; 3D image reconstruction; 3D model; background removal; discrete medial axis; image segmentation; object movie segmentation; shape prior learning; volumetric graph cuts; Computer networks; Computer science; Image reconstruction; Image segmentation; Information science; Motion pictures; Reconstruction algorithms; Shape; Usability; Virtual reality;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.119
Filename
1698898
Link To Document