3D object retrieval with bag-of-region-words

  • Authors:

  • Yue Gao;You Yang;Qionghai Dai;Naiyao Zhang

  • Affiliations:

  • Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China

  • Venue:
  • Proceedings of the international conference on Multimedia
  • Year:
  • 2010

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Abstract

View-based method becomes an essential approach to 3D object retrieval in recent years. In the view-based 3D object retrieval framework, each object is described by a set of views and representative features are extracted from these views to match the objects in database. In this paper, we propose a novel 3D multi-view representation method, Bag-of-Region-Words (BoRW). It first gridly selects points in each view and extracts local SIFT features. Each local feature is encoded into a visual word with a trained visual vocabulary. Then each view is split into several regions, and each region is represented by a bag-of-visual-words feature vector. All the obtained regions are further grouped into clusters based on the bag-of-visual-words feature, and one feature is selected from each cluster with corresponding weight. In this way, each object is described by a set of BoRW. The Earth Movers Distance is employed to estimate the distance between two BoRW feature vectors. Experimental results show that the proposed method can achieve better retrieval performance than existing methods.