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Partitioning Range Images Using Curvature and Scale

Authors: [tex2html_wrap4172]A. Lejeune, F.P. Ferrie

Investigator username: ferrie

Category: perception

Subcategory: active perception

A key problem in the interpretation of visual form is the partitioning of a shape into principal components that correspond to the parts of an object. The key result of this research is a method for partitioning a set of surface estimates obtained with a laser range finding system into subsets corresponding to such parts. The strategy employed makes use of two complementary representations for surfaces: one that describes local structures in terms of differential properties (e.g. edges, lines, contours) and the other that represents the surface as a collection of smooth patches at different scales. It is shown that by enforcing a consistent interpretation between these two representations, it is possible to derive a partitioning algorithm that is both efficient and robust.

The resulting algorithm is highly successful at partitioning range images into regions corresponding to parts for both man-made objects and natural forms.

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baron@cim.mcgill.ca