We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training set. We construct an efficient iterative matching algorithm by learning the relationship between perturbations in the model parameters and the induced image errors.
|Number of pages
|IEEE Transactions on Pattern Analysis and Machine Intelligence
|Published - Jun 2001
- Appearance models
- Deformable templates
- Model matching
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Impact: Technological, Economic, Society and culture
Impact: Health and wellbeing, Economic, Technological