Analyzing the Probability of a False Alarm for the Hausdorff Distance Under Translation

Here is a postscript version of this paper. [181 Kb]


In order for model-based recognition and geometric shape comparison methods to be more useful in practice, we need accurate models for predicting their performance. Over the last several years a number of formal models have been developed for estimating the probability of a false match for model-based recognition methods that are based on geometric feature correspondences. These models can be used to set the parameters of such methods automatically, so as to limit the probability of a randomly occurring match to some pre-specified level. This paper considers the related problem of developing a formal model for the probability of a false match when using the generalized Hausdorff measure. The model enables the parameters of Hausdorff methods (the distance and fraction) to be set so as to produce a desired level of false positive matches.