Paper
4 March 2015 Groupwise surface correspondence using particle filtering
Guangxu Li, Hyoungseop Kim, Joo Kooi Tan, Seiji Ishikawa
Author Affiliations +
Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94432O (2015) https://doi.org/10.1117/12.2179122
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guangxu Li, Hyoungseop Kim, Joo Kooi Tan, and Seiji Ishikawa "Groupwise surface correspondence using particle filtering", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432O (4 March 2015); https://doi.org/10.1117/12.2179122
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KEYWORDS
3D modeling

Particle filters

Spherical lenses

Particles

Statistical modeling

Lung

Data modeling

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