Abstract-Automatic Image Annotation (AIA) is a challenging problem in the field of image retrieval, and several methods have been proposed. However, visually supporting this important tasks and reducing the semantic gap between low-level image features and high-level semantic concepts still remains a key issue. In this paper, we propose a visually supporting image annotation framework based on visual features and ontologies. Our framework relies on three main components: (i) extraction and classification of features component, (ii) ontology's building component and (iii) image annotation component. Our goal consists on improving the visual image annotation by:(1) extracting invariant and complex visual features; (2) integrating feature classification results and semantic concepts to build ontology and (3) combining both visual and semantic similarities during the image annotation process.
In previous work, an image annotation approach based on visual features and ontologies has been proposed REF .
Visually Supporting Image Annotation Based on Visual Features and Ontologies
2017 21st International Conference Information Visualisation (IV)
2017 21st International Conference Information Visualisation (IV)
Computer Science