Model-based objects recognition in industrial environments for autonomous vehicles control
dc.contributor.author
dc.date.accessioned
2010-05-06T09:13:59Z
dc.date.available
2010-05-03T15:10:37Z
2010-05-06T09:13:59Z
dc.date.issued
1997
dc.identifier.citation
Martí, J., Batlle, J., i Casals, A. (1997). Model-based objects recognition in industrial environments for autonomous vehicles control. IEEE International Conference on Robotics and Automation : 1997 : Proceedings, 2, 1632-1637. Recuperat 06 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=614376
dc.identifier.isbn
0-7803-3612-7
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dc.description.abstract
Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system
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application/pdf
dc.language.iso
eng
dc.publisher
IEEE
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/ROBOT.1997.614376
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© IEEE International Conference on Robotics and Automation : 1997 : Proceedings, 1997, vol. 2, p. 1632-1637
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Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Model-based objects recognition in industrial environments for autonomous vehicles control
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi