Goldfeder Corey author Columbia University. Computer Science Allen Peter K. author Columbia University. Computer Science Columbia University. Computer Science originator text Articles 2008 English Text search on databases of 3D models has traditionally worked poorly, as text annotations on 3D models are often unreliable or incomplete. We attempt to improve the recall of text search by automatically assigning appropriate tags to models. Our algorithm finds relevant tags by appealing to a large corpus of partially labeled example models, which does not have to be preclassified or otherwise prepared. For this purpose we use a copy of Google 3D Warehouse, a database of user contributed models which is publicly available on the Internet. Given a model to tag, we find geometrically similar models in the corpus, based on distances in a reduced dimensional space derived from Zernike descriptors. The labels of these neighbors are used as tag candidates for the model with probabilities proportional to the degree of geometric similarity. We show experimentally that text based search for 3D models using our computed tags can approach the quality of geometry based search. Robotics Artificial intelligence Spagnuolo Michela editor Cohen-Or Daniel editor Gu Xianfeng David editor Piscataway, N.J. IEEE 2008 281 282 http://dx.doi.org/0.1109/SMI.2008.4548007 http://hdl.handle.net/10022/AC:P:15129 NNC NNC 2012-10-31 15:02:23 -0400 2012-10-31 15:10:47 -0400 9131 eng