K. M. Andress

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goal of computer vision is the development of systems capable of carrying out scene interpretation while taking into account all the available knowledge In this article, we focus on how the interpretation task can be aided by the expected scene information (such as map knowledge), which, in most cases, would not be in registration with the perceived scene(More)
In this paper, we will review the process of evidence accumulation in the PSEIKI system for expectation-driven interpretation of images of 3-D scenes. Expectations are presented to PSEIKI as a geometrical hierarchy of abstractions. PSEIKI's job is then to construct abstraction hierarchies in the perceived image taking cues from the abstraction hierarchies(More)
World representation is obviously a most important part of the sensory intelligence required by a mobile robot in order to operate autonomously in a complex environment. In this paper, we will propose a taxonomy of robot intelligence based on the methods used for world representation and for the integration of sensory information with the representations.(More)
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