Ontology based complex object recognition

Abstract

This paper presents a new approach for object categorization involving the following aspects of cognitive vision: learning, recognition and knowledge representation. 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. Machine learning techniques are used to solve the symbol grounding problem (i.e. linking meaningfully symbols to sensory information). This paper shows, how a new object categorization system is set up by a knowledge acquisition and learning phase and then used by an object categorization phase.

Raster and Vector Integration for Fuzzy Vector Information Representation Within GIS

“…Concerning the use of raster information to subdivide VU, a comparison (or a combination) with object oriented classification could be done (Maillot, 2008), (Forestier, 2008), (Hudelot, 2008). Object oriented classifications directly start with the raw images divided into elementary raster units (RU) according to a segmentation process (such as Watershed).…”

A Novel Knowledge-Compatibility Benchmarker for Semantic Segmentation

“…It proposes an efficient model that captures the contextual information among more than a hundred of object categories. The work in [17] proposes a visual concept ontology composed of several types of concepts (spatial concepts and relations, color concepts and texture concepts). The ontology knowledge is used to perform complex object categorization.…”

Biological Models for Active Vision: Towards a Unified Architecture

“…There is a wealth of scene understanding systems roughly divided into four major streams: grammars [2][3][4], blackboard architectures [5,6], probabilistic models [7][8][9], and artificial intelligence methods based on ontologies and description logics [10][11][12]. Some systems perform active vision tasks by controlling cameras [13].…”