Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/44092
Title: | Using Fisher kernel on 2D-shape identification | Authors: | Travieso, Carlos M. Briceño, Juan C. Ferrer, Miguel A. Alonso, Jesús B. |
UNESCO Clasification: | 3307 Tecnología electrónica | Keywords: | Support Vector Machines (SVM), 2D-shape, Fisher Kernel, 2D-shape recognition, Hidden Markov Models (HMM) | Issue Date: | 2007 | Publisher: | 0302-9743 | Journal: | Lecture Notes in Computer Science | Conference: | 11th International Conference on Computer Aided Systems Theory | Abstract: | 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 | Source: | 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 |
Appears in Collections: | Actas de congresos |
SCOPUSTM
Citations
1
checked on Feb 9, 2025
WEB OF SCIENCETM
Citations
1
checked on Feb 25, 2024
Page view(s)
53
checked on Feb 10, 2024
Google ScholarTM
Check
Altmetric
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.