3D-Model Retrieval Using Bag-of-Features Based on Closed Curves

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Date
2013
Journal Title
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Volume Title
Publisher
The Eurographics Association
Abstract
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.
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@inproceedings{
:10.2312/3DOR/3DOR13/101-104
, booktitle = {
Eurographics Workshop on 3D Object Retrieval
}, editor = {
Umberto Castellani and Tobias Schreck and Silvia Biasotti and Ioannis Pratikakis and Afzal Godil and Remco Veltkamp
}, title = {{
3D-Model Retrieval Using Bag-of-Features Based on Closed Curves
}}, author = {
Khoury, Rachid El
and
Vandeborre, Jean-Philippe
and
Daoudi, Mohamed
}, year = {
2013
}, publisher = {
The Eurographics Association
}, ISSN = {
1997-0463
}, ISBN = {
978-3-905674-44-6
}, DOI = {
/10.2312/3DOR/3DOR13/101-104
} }
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