Learning rules for 3D object recognition
A fully autonomous computer-vision system needs the ability to automatically learn, or discover, from training views of objects the object information (models) needed for recognition. One approach to object recognition uses an evidence rulebase composed of objects with corresponding degrees of evidence for the various objects in the databases. A technique for automatically deriving the evidence rulebase from training views of objects is presented. This generated rulebase is shown to provide successful recognition of new views of those objects.<<ETX>>