Towards ontology-based cognitive vision

Abstract.This paper details a visual-concept-ontology-driven knowledge acquisition methodology. We propose to use a visual concept ontology to guide experts in the visual description of the objects of their domain (e.g., pollen grain). The proposed knowledge acquisition process results in a knowledge base enabling semantic image interpretation. An important benefit of our approach is that the knowledge acquisition process guided by the ontology leads to a knowledge base close to low-level vision. A visual concept ontology and a dedicated knowledge acquisition tool have been developed and are presented. We propose a generic methodology that is not linked to any application domain. An example shows how the knowledge acquisition model can be applied to the description of pollen grain images.

[1]  Bruce A. Draper,et al.  Knowledge-directed vision: control, learning, and integration , 1996, Proc. IEEE.

[2]  Takashi Matsuyama,et al.  SIGMA: A Knowledge-Based Aerial Image Understanding System , 1990 .

[3]  Ying Dong,et al.  On constructing a cooperative paradigm , 2002, Appl. Artif. Intell..

[4]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[5]  Anthony G. Cohn,et al.  Qualitative Spatial Representation and Reasoning: An Overview , 2001, Fundam. Informaticae.

[6]  Bruce A. Draper,et al.  The schema system , 1988, International Journal of Computer Vision.

[7]  Asunción Gómez-Pérez,et al.  Building Ontologies at the Knowledge Level using the Ontology Design Environment , 1998 .

[8]  R. Moller,et al.  Towards computer vision with description logics: some recent progress , 1999, Proceedings Integration of Speech and Image Understanding.

[9]  M. Berthod,et al.  Automatic classification of planktonic foraminifera by a knowledge-based system , 1994, Proceedings of the Tenth Conference on Artificial Intelligence for Applications.

[10]  G. Miller,et al.  Language and Perception , 1976 .

[11]  Francesco M. Donini,et al.  Structured Knowledge Representation for Image Retrieval , 2011, J. Artif. Intell. Res..

[12]  A. Ravishankar Rao,et al.  The Texture Lexicon: Understanding the Categorization of Visual Texture Terms and Their Relationship to Texture Images , 1997, Cogn. Sci..

[13]  A. Ravishankar Rao,et al.  Towards a texture naming system: Identifying relevant dimensions of texture , 1993, Vision Research.

[14]  Ching-chih Chen,et al.  Using sharable ontology to retrieve historical images , 2002, JCDL '02.

[15]  Monique Thonnat,et al.  Knowledge based classification of galaxies , 1989 .

[16]  Richard Lepage,et al.  Knowledge-Based Image Understanding Systems: A Survey , 1997, Comput. Vis. Image Underst..

[17]  Ramin Zabih,et al.  Comparing images using color coherence vectors , 1997, MULTIMEDIA '96.

[18]  William A. Barrett,et al.  Interactive Segmentation with Intelligent Scissors , 1998, Graph. Model. Image Process..

[19]  Fabien L. Gandon,et al.  Ontology Engineering: a Survey and a Return on Experience , 2002 .

[20]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..