Abstract
Real-world image understanding tasks often involve complex object models which are not adequately represented by a single representational scheme for the various recognition scenarios encountered in practice. Multiple representations, on the other hand, allow different matching strategies to be applied for the same object, or even for different parts of the same object. This paper is concerned with the derivation of hierarchical CAD models having multiple representations — concave/convex edges and straight homogeneous generalized cylinder — and their use for generic object recognition in outdoor visible imagery. It also presents a refocused matching algorithm that uses a hierarchically structured model database to facilitate generic object recognition. Experimental results demonstrating generic recognition of objects in perspective, aerial images are presented.
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