21 August 1987 Symbolic Surface Descriptors For 3-Dimensional Object Recognition
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Proceedings Volume 0754, Optical and Digital Pattern Recognition; (1987) https://doi.org/10.1117/12.939971
Event: OE LASE'87 and EO Imaging Symposium, 1987, Los Angeles, CA, United States
Abstract
We are studying classification of symbolic surface de-scriptors in classes that will allow fast approaches for 3-D object recognition. In our approach for object recognition, we will use features to hypothesize objects using parallel distributed approach, and then use models of objects to find objects that are present in a scene. 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 en-tirely. 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.
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Ramesh Jain, Ramesh Jain, Thawach Sripradisvarakul, Thawach Sripradisvarakul, Nancy O'Brien, Nancy O'Brien, } "Symbolic Surface Descriptors For 3-Dimensional Object Recognition", Proc. SPIE 0754, Optical and Digital Pattern Recognition, (21 August 1987); doi: 10.1117/12.939971; https://doi.org/10.1117/12.939971
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