Ontology Based Object Learning and Recognition : Application to

This paper presents a new object categorization method and shows how it can be used for image retrieval. Our approach involves machine learning and knowledge representation techniques. A major element of our approach is a visual concept ontology composed of several types of concepts (spatial concepts and relations, color concepts and texture concepts) . Visual concepts contained in this ontology can be seen as an intermediate layer between domain knowledge and image processing procedures. Our approach is composed of three phases: (1) a knowledge acquisition phase, (2) a learning phase and (3) a categorization phase. This paper is mainly focused on phases (2) and (3). A major issue is the symbol grounding problem which consists of linking meaningfully symbols to sensory information. We propose a solution to this difficult issue by showing how learning techniques can map numerical features to visual concepts