Abstract
An empirical study of the accuracy of five different curvature
estimation techniques, using synthetic range images and images obtained
from three range sensors, is presented. The results obtained highlight
the problems inherent in accurate estimation of curvatures, which are
second-order quantities, and thus highly sensitive to noise
contamination. The numerical curvature estimation methods are found to
perform about as accurately as the analytic techniques, although
ensemble estimates of overall surface curvature such as averages are
unreliable unless trimmed estimates are used. The median proved to be
the best estimator of location. As an exception, it is shown
theoretically that zero curvature can be fairly reliably detected, with
appropriate selection of threshold values
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