A methodology for evaluating range image segmentation techniques

`Over-segmentation', `under-segmentation', `good results' and similar subjective terms appear frequently in the literature on range image segmentation. However, even though the need for standardized segmentation error metrics has been long recognized, no formal methodology for evaluating a range image segmentation has appeared. This paper describes a framework in which to carry out such an evaluation. With this framework, a more rigorous and objective comparison of range image segmentation techniques can be performed. We have developed many key issues, including a formal deenition of the range image segmentation problem, a comprehensive data set to use in evaluation, a method for creating ground truths, and a set of formally deened metrics to classify segmentation results against ground truths.