A graph-theoretic approach to 3D shape classification

@article{Hamza2016AGA,
  title={A graph-theoretic approach to 3D shape classification},
  author={A. Ben Hamza},
  journal={Neurocomputing},
  year={2016},
  volume={211},
  pages={11-21}
}
Shape classification is an intriguing and challenging problem that lies at the crossroads of computer vision, geometry processing and machine learning. In this paper, we introduce a graph-theoretic approach for 3D shape classification using graph regularized sparse coding in conjunction with the biharmonic distance map. Our unified framework exploits both sparsity and dependence among the features of shape descriptors in a bid to design robust shape signatures that are effective in… CONTINUE READING
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