期刊名称：International Journal of Reviews in Computing
印刷版ISSN：2076-3328
电子版ISSN：2076-3336
出版年度：2010
卷号：3
出版社：Little Lion Scientific Research and Developement
摘要：The increasing number of objects 3D available on the Internet or in specialized databases which require the establishment of methods to develop description and recognition techniques to access intelligently to the contents of these objects. In this context, our work whose objective is to present the methods of invariant description [1,2,3] and recognition of 3D objects based on statistical methods: analysis of data (AD) and the principal component analysis (PCA). The objective of this studies is to determine an invariant description [4,5] of a 3D object using a coefficients vector of canonical correlations from the data analysis. This vector is invariant against affine transformation of the 3D object and recognize the object (s) of a database (3D objects) similar(s) to a given object (query object) using the descriptor vectors extracted from these 3D objects by the principal component analysis.The 3D objects of this database are transformations of 3D objects by one element of the overall transformation. The set of transformations considered in this work is the general affine group. The measure of similarity between two objects is achieved by a similarity function using the Euclidean distance.
关键词：Invariants Descriptors; Recognizing; 3D objects; Multiple Regression; Principal Component Analysis; Affine Transformation
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