3D zernike descriptors for content based shape retrieval

By Marcin Novotni, Reinhard Klein. ACM Symposium on Solid Modeling and Applications, 2003

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A survey of content based 3D shape retrieval methods (2004, methodology): “The discriminative abilities of Osada’s method [66] have been improved by further refinements of distribution methods as well as by several methods based on spatial maps [43, 61, 84].”
A 3D Shape Benchmark for Retrieval and Automatic Classification of Architectural Data (2009, methodology): “For unsupervised retrieval we used global Zernike moments descriptors [Nov03] (GZM), for supervised retrieval we chose the method presented in [WBK08] using local spin-images (LSI) as well as global Zernike moments.”
The Columbia grasp database (2009, methodology): “Our second method used L(2) distances between Zernike descriptors [15].”
Context-based search for 3D models (2010, methodology): “We use the 3D Zernike descriptors [Novotni and Klein 2003].”