In this paper

we propose a novel 3D model retrieval algorithm based on Relative angle-distribution and clustering (RAC). A geometric feature vector based on relative-angle distribution (RAD) of surface points is defined. The experimental results demonstrate that RAD is a good global feature for shape classification. To reduce the feature dimensions and improve the computational efficiency

clustering is employed. The model classification results show that compared with other methods

our algorithm RAC (relative angle clustering) achieves better retrieval accuracy and efficiency.