Using Fisher Kernel on 2D-Shape Identification
Identifieur interne : 000D80 ( Main/Exploration ); précédent : 000D79; suivant : 000D81Using Fisher Kernel on 2D-Shape Identification
Auteurs : M. Travieso [Espagne] ; C. Brice O [Costa Rica] ; A. Ferrer [Espagne] ; B. Alonso [Espagne]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
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.
Url:
DOI: 10.1007/978-3-540-75867-9_93
Affiliations:
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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.</div></front></TEI><affiliations><list><country><li>Costa Rica</li><li>Espagne</li></country></list><tree><country name="Espagne"><noRegion><name sortKey="Travieso, M" sort="Travieso, M" uniqKey="Travieso M" first="M." last="Travieso">M. Travieso</name></noRegion><name sortKey="Alonso, B" sort="Alonso, B" uniqKey="Alonso B" first="B." last="Alonso">B. 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