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Proceedings Paper

Groupwise surface correspondence using particle filtering
Author(s): Guangxu Li; Hyoungseop Kim; Joo Kooi Tan; Seiji Ishikawa
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Paper Abstract

To obtain an effective interpretation of organic shape using statistical shape models (SSMs), the correspondence of the landmarks through all the training samples is the most challenging part in model building. In this study, a coarse-tofine groupwise correspondence method for 3-D polygonal surfaces is proposed. We manipulate a reference model in advance. Then all the training samples are mapped to a unified spherical parameter space. According to the positions of landmarks of the reference model, the candidate regions for correspondence are chosen. Finally we refine the perceptually correct correspondences between landmarks using particle filter algorithm, where the likelihood of local surface features are introduced as the criterion. The proposed method was performed on the correspondence of 9 cases of left lung training samples. Experimental results show the proposed method is flexible and under-constrained.

Paper Details

Date Published: 4 March 2015
PDF: 7 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432O (4 March 2015); doi: 10.1117/12.2179122
Show Author Affiliations
Guangxu Li, Tianjin Polytechnic Univ. (China)
Hyoungseop Kim, Kyushu Institute of Technology (Japan)
Joo Kooi Tan, Kyushu Institute of Technology (Japan)
Seiji Ishikawa, Kyushu Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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