3D-Model Retrieval Using Bag-of-Features Based on Closed Curves
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Date
2013
Journal Title
Journal ISSN
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.
Description
@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}
}