Rapid and Effective Segmentation of 3D Models using Random Walks

Yu-Kun Lai Tsinghua University Shi-Min Hu Tsinghua University Ralph R. Martin Cardiff University Paul L. Rosin Cardiff University

Geometric Modeling and Processing mathscidoc:1608.16052

Computer Aided Geometric Design, 26, (6), 665-679., 2009
3D models are now widely available for use in various applications. The demand for automatic model analysis and understanding is ever increasing. Model segmentation is an important step towards model understanding, and acts as a useful tool for different model processing applications, e.g. reverse engineering and modeling by example. We extend a random walk method used previously for image segmentation to give algorithms for both interactive and automatic model segmentation. This method is extremely efficient, and scales almost linearly with the number of faces, and the number of regions. For models of moderate size, interactive performance is achieved with commodity PCs. We demonstrate that this method can be applied to both triangle meshes and point cloud data. It is easy to implement, robust to noise in the model, and yields results suitable for downstream applications for both graphical and engineering models.
Segmentation, Random Walks
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@inproceedings{yu-kun2009rapid,
  title={Rapid and Effective Segmentation of 3D Models using Random Walks},
  author={Yu-Kun Lai, Shi-Min Hu, Ralph R. Martin, and Paul L. Rosin},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160823082257766301396},
  booktitle={Computer Aided Geometric Design},
  volume={26},
  number={6},
  pages={665-679.},
  year={2009},
}
Yu-Kun Lai, Shi-Min Hu, Ralph R. Martin, and Paul L. Rosin. Rapid and Effective Segmentation of 3D Models using Random Walks. 2009. Vol. 26. In Computer Aided Geometric Design. pp.665-679.. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160823082257766301396.
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