arXiv · 1012.2491
Affine Invariant, Model-Based Object Recognition Using Robust Metrics and Bayesian Statistics
Abstract
We revisit the problem of model-based object recognition for intensity images and attempt to address some of the shortcomings of existing Bayesian methods, such as unsuitable priors and the treatment of residuals with a non-robust error norm. We do so by using a refor- mulation of the Huber metric and carefully chosen prior distributions. Our proposed method is invariant to 2-dimensional affine transforma- tions and, because it is relatively easy to train and use, it is suited for general object matching problems.
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Vasileios Zografos, Bernard Buxton. 2010-12-11. Affine Invariant, Model-Based Object Recognition Using Robust Metrics and Bayesian Statistics. https://doi.org/10.1007/11559573_51
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