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Estimating the Pen Trajectories of Handwritten Static Scripts using Hidden Markov Models

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If you have a question about this talk, please contact David MacKay .

Static handwritten scripts originate as images on documents and do not, by definition, contain any dynamic information. In this talk, it will be shown how one can estimate dynamic information from handwritten static images by constructing hierarchical hidden Markov models from the images, and matching dynamic training data to the constructed models. The efficacy of our approach is demonstrated with quantitative results and some practical examples.

This talk is part of the Inference Group series.

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