Minimum Near-Convex Shape Decomposition

  title={Minimum Near-Convex Shape Decomposition},
  author={Zhou Ren and Junsong Yuan and Wenyu Liu},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
Shape decomposition is a fundamental problem for part-based shape representation. We propose the minimum near-convex decomposition (MNCD) to decompose arbitrary shapes into minimum number of "near-convex" parts. The near-convex shape decomposition is formulated as a discrete optimization problem by minimizing the number of nonintersecting cuts. Two perception rules are imposed as constraints into our objective function to improve the visual naturalness of the decomposition. With the degree of… CONTINUE READING
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Minimum Convex Decomposition, ~snoeyink/demos/convdecomp

  • J. M. Keil, J. Snoeyink
  • 2007
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