A Nonlinear Discriminative Approach to AAM Fitting
- 1 January 2007
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The Active Appearance Model (AAM) is a powerful generative method for modeling and registering deformable visual objects. Most methods for AAM fitting utilize a linear parameter update model in an iterative framework. Despite its popularity, the scope of this approach is severely restricted, both in fitting accuracy and capture range, due to the simplicity of the linear update models used. In this paper, we present an new AAM fitting formulation, which utilizes a nonlinear update model. To motivate our approach, we compare its performance against two popular fitting methods on two publicly available face databases, in which this formulation boasts significant performance improvements.Keywords
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