Using Fisher kernel on 2D-shape identification

Título:	Using Fisher kernel on 2D-shape identification
Autores/as:	Travieso, Carlos M. Briceño, Juan C. Ferrer, Miguel A. Alonso, Jesús B.
Clasificación UNESCO:	3307 Tecnología electrónica
Palabras clave:	Support Vector Machines (SVM), 2D-shape, Fisher Kernel, 2D-shape recognition, Hidden Markov Models (HMM)
Fecha de publicación:	2007
Editor/a:	0302-9743
Publicación seriada:	Lecture Notes in Computer Science
Conferencia:	11th International Conference on Computer Aided Systems Theory
Resumen:	This paper proposes to use the Fisher kernel for planar shape recognition. A synthetic experiment with artificial shapes has been built. The difference among shapes is the number of vertexes, links between vertexes, size and rotation. The 2D-shapes are parameterized with sweeping angles in order to obtain scale and rotation invariance. A Hidden Markov Model is used to obtain the Fisher score which feeds the Support Vector Machine based classifier. Noise has been added to the shapes in order to check the robustness of the system against noise. Hit ratio score over 99%, has been obtained, which shows the ability of the Fisher kernel tool for planar shape recognition.
URI:	http://hdl.handle.net/10553/44092
ISBN:	9783540758662
ISSN:	0302-9743
Fuente:	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 4739 LNCS, p. 740-746
Colección:	Actas de congresos

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