Towards a general vision system based on symbol-relation grammars and Bayesian networks

Authors:
Elias Ruiz;Augusto Melendez;L. Enrique Sucar
Affiliations:
Computer Science Department, National Institute of Astrophysics, Optics and Electronics, Tonantzitla, México;Computer Science Department, National Institute of Astrophysics, Optics and Electronics, Tonantzitla, México;Computer Science Department, National Institute of Astrophysics, Optics and Electronics, Tonantzitla, México
Venue:
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Year:
2011

Citing 6
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Abstract

A novel approach to create a general vision system is presented. The proposed method is based on a visual grammar representation which is transformed to a Bayesian network which is used for object recognition. We use a symbol-relational grammar for a hierarchical description of objects, incorporating spatial relations. The structure of a Bayesian network is obtained automatically from the grammar, and its parameters are learned from examples. The method is illustrated with two examples for face recognition.