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Matching non-rigid shapes is a challenging research field in content-based 3D object retrieval. In this paper, we present an image-based method to effectively address this problem. Multidimensional Scaling (MDS) and Principal Component Analysis (PCA) are first applied to each object to calculate its canonical form, which is afterward represented by 66 depthbuffer images captured on the vertices of an unit geodesic sphere. Then, each image is described as a word histogram obtained by the vectordoi:10.1109/icip.2010.5654226 dblp:conf/icip/LianGSZ10 fatcat:jffbfcq3dnfbxax4vzfahelbpy