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Type: Artigo de evento
Title: Image Categorization Through Optimum Path Forest And Visual Words
Author: Papa J.P.
Rocha A.
Abstract: Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.
Citation: Proceedings - International Conference On Image Processing, Icip. , v. , n. , p. 3525 - 3528, 2011.
Rights: fechado
Identifier DOI: 10.1109/ICIP.2011.6116475
Date Issue: 2011
Appears in Collections:Unicamp - Artigos e Outros Documentos

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