Abstract
The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve 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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Karhunen–Loève theoremArtificial intelligenceCovariance matrixEigenfunctionHomogeneous spaceMathematicsSet (abstract data type)Computer scienceBasis (linear algebra)Extension (predicate logic)Matrix (chemical analysis)Pattern recognition (psychology)AlgorithmEigenvalues and eigenvectorsPhysicsGeometry
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Publication Info
- Year
- 1990
- Type
- article
- Volume
- 12
- Issue
- 1
- Pages
- 103-108
- Citations
- 2448
- Access
- Closed
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Cite This
Michael Kirby,
L. Sirovich
(1990).
Application of the Karhunen-Loeve procedure for the characterization of human faces.
IEEE Transactions on Pattern Analysis and Machine Intelligence
, 12
(1)
, 103-108.
https://doi.org/10.1109/34.41390
Identifiers
- DOI
- 10.1109/34.41390