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IMAGE CATEGORIZATION THROUGH OPTIMUM PATH FOREST AND VISUAL WORDS

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Autor(es):
Papa, Joao Paulo ; Rocha, Anderson ; IEEE
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: 2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP); v. N/A, p. 4-pg., 2011-01-01.
Resumo

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. (AU)

Processo FAPESP: 09/16206-1 - Novas tendências em reconhecimento de padrões baseado em floresta de caminhos ótimos
Beneficiário:João Paulo Papa
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
Processo FAPESP: 10/05647-4 - Computação forense e criminalística de documentos: coleta, organização, classificação e análise de evidências
Beneficiário:Anderson de Rezende Rocha
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores