Abstract
A novel robust active appearance model (AAM) matching algorithm is presented. The method consists of two main stages. First, initial residuals are clustered by a non parametric mean shift mode detection step. Second, modes without gross outliers are selected using an objective function. Robustness of the matching procedure is demonstrated on a variety of examples with different noise conditions. The proposed algorithm outperformed the conventional AAM matching on images with gross disturbances and can tolerate up to 40% of disturbed data.
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Beichel, R., Bischof, H., Leberl, F., Sonka, M. (2005). Robust Active Appearance Model Matching. In: Christensen, G.E., Sonka, M. (eds) Information Processing in Medical Imaging. IPMI 2005. Lecture Notes in Computer Science, vol 3565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11505730_10
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DOI: https://doi.org/10.1007/11505730_10
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