| Texto completo | |
| Autor(es): |
Afonso, L.
;
Papa, J.
;
Papa, L.
;
Marana, A.
;
Rocha, Anderson
;
IEEE
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2012 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2012); v. N/A, p. 4-pg., 2012-01-01. |
| Resumo | |
Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. (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 |