Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/16113
Title: Exploring the use of local descriptors for fish recognition in LifeCLEF 2015
Authors: Cabrera-Gámez, Jorge 
Castrillón-Santana, Modesto 
Domínguez-Brito, Antonio 
Hernández Sosa, José Daniel 
Isern-González, Josep 
Lorenzo-Navarro, Javier 
UNESCO Clasification: 120304 Inteligencia artificial
120325 Diseño de sistemas sensores
Issue Date: 2015
Journal: CEUR Workshop Proceedings 
Conference: 16th Conference and Labs of the Evaluation Forum, CLEF 2015 
Abstract: This paper summarizes the proposal made by the SIANI team for the LifeCLEF 2015 Fish task. The approach makes use of standard detection techniques, applying a multiclass SVM based classifier on large enough Regions Of Interest (ROIs) automatically extracted from the provided video frames. The selection of the detection and classification modules is based on the best performance achieved for the validation dataset consisting of 20 annotated videos. For that dataset, the best classification achieved for an ideal detection module, reaches an accuracy around 40%.
URI: http://hdl.handle.net/10553/16113
ISSN: 1613-0073
Source: CEUR Workshop Proceedings[ISSN 1613-0073],v. 1391
Appears in Collections:Actas de congresos
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