Combination of Variant 2D Cepstral Features for 3D Model Retrieval

In this paper, we will propose a 3D model retrieval approach using variant 2D cepstral features. First, six projection images, which represents the depth information from the model surface to the projection planes corresponding to six different viewing directions, are generated. Then, variant 2D cepstral features, obtained by using different subband decomposition methods, are extracted from each projection image to describe each 3D models. Experiments conducted on the Princeton Shape Benchmark (PSB) database have shown that the proposed 2D cepstral features outperforms other state-of-the-art descriptors in terms of the discounted cumulative gain (DCG) value.