APPLICATION OF THE KARHUNEN-LOEVE PROCEDURE FOR THE CHARACTERIZATION OF HUMAN FACES

被引：1398

作者：

KIRBY, M

SIROVICH, L

机构：

[1] Center for Fluid Mechanics, Turbulence, and Computation, Division of Applied Mathematics, Brown University, Providence

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1990年 / 12卷 / 01期

关键词：

Data compression; Data extension; Face characterization; Karhunen-Loève expansion; Symmetric eigenfunctions;

D O I：

10.1109/34.41390

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The exploitation of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loéve expansion. This results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix, without increasing the complexity of the calculation. The resulting approximation of faces projected from outside of the data set onto this optimal basis is improved on average. © 1990 IEEE.

引用

页码：103 / 108

页数：6

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