In modern visual information retrieval systems, visual content is directly addressed by features such as color, texture, shape and spatial relationship. While a large amount of work is being done around the perceptual soundness of models and around the automatic extraction of features, only a limited amount of attention is being placed on the combination of useful representations and similarity models with efficient index structures for shape. In this paper, we discuss retrieval by shape similarity using local features and metric indexing. Shape is partitioned into tokens in correspondence with its protrusions, following curvature analysis. Each token is modeled by a set of perceptually salient attributes, and two distinct distance functions are used to model token similarity and shape similarity. Shape indexing is obtained by arranging shape tokens into a M-tree index structure, suitably modified. Examples from a prototype system are expounded with considerations about the effectiveness of the approach and a comparative performance analysis.

RETRIEVAL BY SHAPE USING MULTIDIMENSIONAL INDEXING STRUCTURES / S. BERRETTI; A. DEL BIMBO; P. PALA. - STAMPA. - (1999), pp. 945-950. (Intervento presentato al convegno ICIAP99, INT. CONF. ON IMAGE ANALYSIS AND PROCESSING tenutosi a VENEZIA, Italy nel September 27-29) [10.1109/ICIAP.1999.797717].

RETRIEVAL BY SHAPE USING MULTIDIMENSIONAL INDEXING STRUCTURES

BERRETTI, STEFANO;DEL BIMBO, ALBERTO;PALA, PIETRO
1999

Abstract

In modern visual information retrieval systems, visual content is directly addressed by features such as color, texture, shape and spatial relationship. While a large amount of work is being done around the perceptual soundness of models and around the automatic extraction of features, only a limited amount of attention is being placed on the combination of useful representations and similarity models with efficient index structures for shape. In this paper, we discuss retrieval by shape similarity using local features and metric indexing. Shape is partitioned into tokens in correspondence with its protrusions, following curvature analysis. Each token is modeled by a set of perceptually salient attributes, and two distinct distance functions are used to model token similarity and shape similarity. Shape indexing is obtained by arranging shape tokens into a M-tree index structure, suitably modified. Examples from a prototype system are expounded with considerations about the effectiveness of the approach and a comparative performance analysis.
1999
Image Analysis and Processing, 1999. Proceedings. International Conference on
ICIAP99, INT. CONF. ON IMAGE ANALYSIS AND PROCESSING
VENEZIA, Italy
September 27-29
S. BERRETTI; A. DEL BIMBO; P. PALA
File in questo prodotto:
File Dimensione Formato  
iciap99.pdf

Accesso chiuso

Descrizione: documento finale
Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: Tutti i diritti riservati
Dimensione 118.65 kB
Formato Adobe PDF
118.65 kB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/3503
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? ND
social impact