View-based 3D model retrieval using two-level spatial structure

Recently, the view-based 3D model retrieval methods have received great research attentions. However, these methods are difficult to preserve the spatial structure of 3D models. In this paper, we propose a novel view-based 3D model retrieval method to solve this problem. Our method is based on the two-level (3D model-level and 2D image-level) spatial structure. Firstly, we extract the spatial structure circular descriptor (SSCD) images from 3D models. The SSCD images can preserve the spatial structure on the 3D model-level. Then, we modify the bag-of-features (BOF) method to extract view-based features from these SSCD images. The modified BOF method can preserve the spatial structure on the 2D image-level. Finally, we calculate the similarity between the query model and the models in the databases by adapting the earth mover distance method. Experimental results show that our method can achieve satisfactory retrieval performance for both the articulated models and the rigid models.