Planning multiple observations for specular object recognition

The most prominent features of specular objects are the specularities, which are highly variable and dependent on local object geometry. In order to unambiguously recognize specular objects, more information is required. An approach for specular object recognition that relies on the use of multiple observations from different viewpoints to resolve any ambiguity in scene interpretation is presented. The results show that the multiple observation strategy can be very accurate, and is in fact limited only by the accuracy with which decisions can be made about individual observations