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Communication Dans Un Congrès Année : 2010

3D-shape retrieval using curves and HMM

Olivier Colot
Mohamed Daoudi

Résumé

In this paper, we propose a new approach for 3D-shape matching. This approach encloses an off-line step and an on-line step. In the off-line one, an alphabet, of which any shape can be composed, is constructed. First, 3D-objects are subdivided into a set of 3D-parts. The subdivision consists to extract from each object a set of feature points with associated curves. Then the whole set of 3D-parts is clustered into different classes from a semantic point of view. After that, each class is modeled by a Hidden Markov Model (HMM). The HMM, which represents a character in the alphabet, is trained using the set of curves corresponding to the class parts. Hence, any 3D-object can be represented by a set of characters. The on-line step consists to compare the set of characters representing the 3D-object query and that of each object in the given dataset. The experimental results obtained on the TOSCA dataset show that the system efficiently performs in retrieving similar 3D-models.
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Dates et versions

hal-00667989 , version 1 (08-02-2012)

Identifiants

  • HAL Id : hal-00667989 , version 1

Citer

Hedi Tabia, Olivier Colot, Mohamed Daoudi, Jean-Philippe Vandeborre. 3D-shape retrieval using curves and HMM. 20th IEEE International Conference on Pattern Recognition (ICPR 2010), Aug 2010, Istanbul, Turkey. pp.WeBCT9.6. ⟨hal-00667989⟩
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