Segmenting Shape Using Deformation Information

Ruiqi GUO  Shinichiro OMACHI  Hirotomo ASO 

Publication
IEICE TRANSACTIONS on Information and Systems  Vol.E92-D  No.6  pp.1296-1303
Publication Date: 2009/06/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
Keyword: 
shape segmentation,  shape matching,  deformation model,  graph partition, 

Full Text: PDF(1.1MB)

Summary: 
To segment a shape into parts is an important problem in shape representation and analysis. We propose in this paper a novel framework of shape segmentation using deformation models learned from multiple shapes. The deformation model from the target image to every other image is then estimated. Finally, normalized-cut graph partition is applied to the graph constructed based on the similarity of local patches in the target image, and a segmentation of the shape is carried out. Experimental results for images from MPEG7 shape database show the effectiveness of the proposed method.