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Issue No.02 - February (1992 vol.14)
pp: 125-145
ABSTRACT
<p>The authors present an approach for the recognition of multiple 3-D object models from three 3-D scene data. The approach uses two different types of primitives for matching: small surface patches, where differential properties can be reliably computed, and lines corresponding to depth or orientation discontinuities. These are represented by splashes and 3-D curves, respectively. It is shown how both of these primitives can be encoded by a set of super segments, consisting of connected linear segments. These super segments are entered into a table and provide the essential mechanism for fast retrieval and matching. The issues of robustness and stability of the features are addressed in detail. The acquisition of the 3-D models is performed automatically by computing splashes in highly structured areas of the objects and by using boundary and surface edges for the generation of 3-D curves. The authors present results with the current system (3-D object recognition based on super segments) and discuss further extensions.</p>
INDEX TERMS
3D object models; pattern recognition; 3D curves; segmentation; small surface patches; orientation discontinuities; super segments; linear segments; pattern recognition; picture processing
CITATION
F. Stein, G. Medioni, "Structural Indexing: Efficient 3-D Object Recognition", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.14, no. 2, pp. 125-145, February 1992, doi:10.1109/34.121785
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