Abstract
Object recognition plays a very important role in many stages of manufacturing. In this paper, we discuss our approach to recognizing objects in range images using CAD databases. The models in the databases will be used to generate recognition strategies. We present some results on symbolic surface descriptors that will play an important role in both the generation of the strategy and in the recognition of objects. Symbolic surface descriptors represent global features of an object and do not change when the object is partially occluded, while local features (such as corners or edges) may disappear entirely. We have developed a technique to segment surfaces and compute their polynomial surface descriptors. In this paper we present results of our study to determine which different types of surface descriptors (such as cylindrical, spherical, elliptical, hyperbolic, etc.) can be reliably recovered from biquadratic equation models of various surfaces.
This research was supported by NSF Grant No. DMC-8520602 and AFOSR Contract No. F33615-85-C-5105.
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© 1988 Springer-Verlag Berlin Heidelberg
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Jain, R., Sripradisvarakul, T., O’Brien, N. (1988). Symbolic Surface Descriptors. In: Jain, A.K. (eds) Real-Time Object Measurement and Classification. NATO ASI Series, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83325-0_16
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DOI: https://doi.org/10.1007/978-3-642-83325-0_16
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