Shape alignment and shape orientation analysis-based 3D shape retrieval system

In this paper, we realized an efficient 3D shape retrieval system based on shape alignment and shape orientation analysis. In this system, we suggest extracting the spatial orientation of the polygon surfaces as the feature of one 3D shape. This information is analyzed by multiresolution wavelet analysis, and the low frequency components are applied to the feature vector. In the preprocessing stage, we adopt four methods of shape alignment including principal component analysis, continuous principal component analysis, normal-based principal component analysis, and plane reflection symmetry analysis (PRSA). We investigated the influence of four alignment methods on retrieval performance. In the orientation sampling stage, the sampling planes are placed on a cube and a dodecahedron, respectively. We also investigated the influence of this two sampling methods on retrieval performance. Finally, one shape descriptor based on plane reflection symmetry analysis and dodecahedron sampling plane (PRSA-DOD) is proposed. We compare this novel shape descriptor, PRSA-DOD descriptor, with the previous methods on Princeton shape benchmark, and results show that this method achieves the higher retrieval performance. This PRSA-DOD descriptor is selected to construct the search engine of system; in the system, the retrieval interface and search engine are implemented.