A Probabilistic Formulation for Hausdor
نویسنده
چکیده
Matching images based on a Hausdorr measure has become popular for computer vision applications. However, no probabilistic model has been used in these applications. This limits the formal treatment of several issues, such as feature uncertainties and prior knowledge. In this paper, we develop a probabilis-tic formulation of image matching in terms of maximum likelihood estimation that generalizes a version of Hausdorr matching. This formulation yields several beneets with respect to previous Hausdorr matching formulations. In addition, we show that the optimal model position in a discretized pose space can be located eeciently in this formation and we apply these techniques to a mobile robot self-localization problem.
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