We present an active object recognition strategy which combines the use of an attention mechanism for focusing the search for a 3-D object in a 2-D image, with a viewpoint control strategy for disambiguating recovered...
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In this paper, we track changes in the appearance of the object as it moves from one frame to the next. At a symbolic level, an aspect graph clusters all the views of an object into a set of topologically distinct cla...
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In this paper, we track changes in the appearance of the object as it moves from one frame to the next. At a symbolic level, an aspect graph clusters all the views of an object into a set of topologically distinct classes in terms of which surfaces of an object are visible from a given viewpoint (Koenderink and van Doom (1979). Two nodes (or aspects) in the aspect graph are connected by an arc if it is possible to directly move from a viewpoint in which the first aspect is visible to a viewpoint in which the second aspect is visible. Qualitatively, we can envision a tracking strategy which simply tracks an object as it moves from one node to another in the object's aspect graph. Although it does not provide us with accurate pose of the object, it does qualitatively describe the motion of the object without the need for a CAD representation of the object.< >
We describe a robot vision system that achieves complex object recognition with two layers of behaviors, performing the tasks of planning and object recognition, respectively. The recognition layer is a pipeline in wh...
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