In this paper we describe a model-based object identification system. Given a set of 3D objects and a scene containing one or more of these objects, the system identifies which objects appear in the scene by matching surface signatures. Surface signatures are statistical features which are uniform for a uniform surface. Two types of surfaces are employed; curvature signatures and spectral signatures. Furthermore, the system employs an inexpensive acquisition setup consisting of a single CCD camera and two light sources. The system has been tested on 95 observed-surfaces and 77 objects of varying degrees of curvature and color with good results.
CITATION STYLE
Mustafa, A. A. Y., Shapiro, L. G., & Ganter, M. A. (1997). Object identification with surface signatures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1296, pp. 58–65). Springer Verlag. https://doi.org/10.1007/3-540-63460-6_100
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