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Erschienen in:
2008 | OriginalPaper | Buchkapitel
A Learning Approach to 3D Object Representation for Classification
verfasst von : Indriyati Atmosukarto, Linda G. Shapiro
Erschienen in: Structural, Syntactic, and Statistical Pattern Recognition
Verlag: Springer Berlin Heidelberg
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In this paper we describe our 3D object signature for 3D object classification. The signature is based on a learning approach that finds salient points on a 3D object and represent these points in a 2D spatial map based on a longitude-latitude transformation. Experimental results show high classification rates on both pose-normalized and rotated objects and include a study on classification accuracy as a function of number of rotations in the training set.