Template Matching: Matched Spatial Filters and Beyond


Autoria(s): Brunelli, Roberto; Poggio, Tomaso
Data(s)

08/10/2004

08/10/2004

01/10/1995

Resumo

Template matching by means of cross-correlation is common practice in pattern recognition. However, its sensitivity to deformations of the pattern and the broad and unsharp peaks it produces are significant drawbacks. This paper reviews some results on how these shortcomings can be removed. Several techniques (Matched Spatial Filters, Synthetic Discriminant Functions, Principal Components Projections and Reconstruction Residuals) are reviewed and compared on a common task: locating eyes in a database of faces. New variants are also proposed and compared: least squares Discriminant Functions and the combined use of projections on eigenfunctions and the corresponding reconstruction residuals. Finally, approximation networks are introduced in an attempt to improve filter design by the introduction of nonlinearity.

Formato

1400743 bytes

1241520 bytes

application/postscript

application/pdf

Identificador

AIM-1549

http://hdl.handle.net/1721.1/6644

Idioma(s)

en_US

Relação

AIM-1549