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- W2242370086 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." @default.
- W2242370086 created "2016-06-24" @default.
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- W2242370086 date "2013-05-11" @default.
- W2242370086 modified "2023-10-15" @default.
- W2242370086 title "3D-model retrieval using bag-of-features based on closed curves" @default.
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