| Texto completo | |
| Autor(es): |
Rocha, Anderson
;
Almeida, Jurandy
;
Nascimento, Mario A.
;
Torres, Ricardo
;
Goldenstein, Siome
;
BlancTalon, J
;
Bourennane, S
;
Philips, W
;
Popescu, D
;
Scheunders, P
Número total de Autores: 10
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Lecture Notes in Computer Science; v. 5259, p. 2-pg., 2008-01-01. |
| Resumo | |
Content-Based Image Retrieval is a challenging problem both in terms of effectiveness and efficiency. In this paper, we present a flexible cluster-and-search approach that is able to reuse any previously proposed image descriptor as long as a suitable similarity function is provided. In the clustering step, the image data set is clustered using a hybrid divisive-agglomerative hierarchical clustering technique. The obtained clusters are organized in a tree that can be traversed efficiently using the similarity function associated with the chosen image descriptors. Our experiments have shown that we can improve search-time performance by a factor of 10 or more, at the cost of small loss in effectiveness (typically less than 15%) when compared to the state-of-the-art solutions. (AU) | |
| Processo FAPESP: | 05/58103-3 - Classificadores e aprendizado em processamento de imagens e visão computacional |
| Beneficiário: | Anderson de Rezende Rocha |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |
| Processo FAPESP: | 05/52959-3 - Estudo e implementacao de tecnicas de descricao de modelos tridimensionais. |
| Beneficiário: | Jurandy Gomes de Almeida Junior |
| Modalidade de apoio: | Bolsas no Brasil - Mestrado |