Evaluation of random forests on large-scale classification problems using a bag-of-visual-words representation

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Title:	Evaluation of random forests on large-scale classification problems using a bag-of-visual-words representation
Author:	Soler, Xavier; Ramisa Ayats, Arnau; Torras, Carme
Other authors:	Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
Abstract:	Random Forest is a very efficient classification method that has shown success in tasks like image segmentation or object detection, but has not been applied yet in large-scale image classification scenarios using a Bag-of-Visual-Words representation. In this work we evaluate the performance of Random Forest on the ImageNet dataset, and compare it to standard approaches in the state-of-the-art.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Informàtica::Automàtica i control -computer vision -image classification -large-scale image classification -classifier forest -random forests -Classificació INSPEC::Pattern recognition::Computer vision
Rights:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Submitted version Conference Object
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