Representation and retrieval of images by means of spatial relations between objects
N/D
Tipo de produção
Artigo de evento
Data de publicação
2019-03-25
Periódico
CEUR Workshop Proceedings
Editor
Texto completo na Scopus
Citações na Scopus
0
Autores
NUNES, D.
FERREIRA, L. A.
Paulo Santos
PEASE, A.
Orientadores
Resumo
Copyright held by the author(s).The present work addresses the challenge of integrating low-level information with high-level knowledge (known as semantic gap) that exists in content-based image retrieval by introducing an approach to describe images by means of spatial relations. The proposed approach is called Image Retrieval using Region Analysis (IRRA) and relies on decomposing images into pairs of objects. This method generates a representation composed of n triples, each one containing: a noun, a preposition and, another noun. This representation paves the way to enable image retrieval based on spatial relations. Results for an indoor/outdoor classifier shows that neural networks alone are capable of achieving 88% in precision and recall, but when combined with ontology this result increases in 10 percentage points, reaching 98% of precision and recall.
Citação
NUNES, D.; FERREIRA, L. A.; SANTOS, P.; PEASE, A. Representation and retrieval of images by means of spatial relations between objects. CEUR Workshop Proceedings, v. 2350, mar. 2019.
Palavras-chave
Keywords
Assuntos Scopus
Content based image retrieval; High level knowledge; Indoor/outdoor; Percentage points; Precision and recall; Region analysis; Semantic gap; Spatial relations