%0 Journal Article
%A CAI Qiang
%A DONG Shui-long
%A DU Jun-ping
%A LI Hai-sheng
%A ZHAO Tian-yu
%T Improved Light Field Descriptor Using Depth Images for 3D Model Retrieval
%D 2016
%R 10.13190/j.jbupt.2016.04.011
%J Journal of Beijing University of Posts and Telecommunications
%P 56-59
%V 39
%N 4
%X Due to the problem of light field descriptor lacking spatial information of 3D model, and the problem of little projection of PANORAMA descriptor, a 3D model retrieval algorithm combining depth image was proposed. The depth images are used to improve light field descriptor. Discrete wavelet transform features and Zernike moments are extracted from projection views. Then the depth images are clustered to remove redundancy. The random walk algorithm is employed to determine the weight of each cluster. Finally, the retrieval method of PANORAMA is optimized to calculate similarity distance between two 3D models. Results on princeton shape benchmark show that the proposed algorithm can make good use of spatial information of 3D model and improve the accuracy of retrieval.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2016.04.011