3D-model retrieval using bag-of-features based on closed curves

Rachid El Khoury (1, 2) , Jean-Philippe Vandeborre (1, 2) , Mohamed Daoudi (1, 2)

1 LIFL - FOX MIIRE
2 Institut TELECOM/TELECOM Lille1

Bag-of-feature technique is a popular approach in areas of computer vision and pattern recognition. Recently, it plays an important role in shape analysis community and especially in 3D-model retrieval. We present our approach for partial 3D-model retrieval using this technique based on closed curves. We define an invariant scalar function on the surface based on the commute-time distance. Our mapping function respects important properties in order to compute robust closed curves. Each scale of our scalar function detects a small region. The form of these regions are encoded in the form of the closed curves. We generate a collection of closed curves from a source point detected automatically. Based on the collection of all closed curves extracted, we construct our bag-of-features. Then we cluster the bag-of-features in the sense in accurate categorization. The centres of classes are defined as keyshapes. This method is particularly interesting in the sense of quantifying the 3D-model by its keyshapes that are accumulated into an histogram. The results shows the robustness of our method (BOF) compared to a method based on indexed closed curves (ICC) on various 3D-models with different poses.

Mots clés: 3D-mesh; recognition; indexing; curves; bag-of-features

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Rachid El Khoury, Jean-Philippe Vandeborre, Mohamed Daoudi. 3D-model retrieval using bag-of-features based on closed curves. Eurographics 2013 Workshop on 3D Object Retrieval, May 2013, Girona, Spain. 3DOR2013 - short paper. ⟨hal-00806609⟩