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Active Appearance Models Revisited (2003)

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by Iain Matthews , Simon Baker
Venue:International Journal of Computer Vision
Citations:462 - 39 self
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BibTeX

@ARTICLE{Matthews03activeappearance,
    author = {Iain Matthews and Simon Baker},
    title = {Active Appearance Models Revisited},
    journal = {International Journal of Computer Vision},
    year = {2003},
    volume = {60},
    pages = {135--164}
}

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Abstract

Active Appearance Models (AAMs) and the closely related concepts of Morphable Models and Active Blobs are generative models of a certain visual phenomenon. Although linear in both shape and appearance, overall, AAMs are nonlinear parametric models in terms of the pixel intensities. Fitting an AAM to an image consists of minimizing the error between the input image and the closest model instance; i.e. solving a nonlinear optimization problem. We propose an efficient fitting algorithm for AAMs based on the inverse compositional image alignment algorithm. We show how the appearance variation can be "projected out" using this algorithm and how the algorithm can be extended to include a "shape normalizing" warp, typically a 2D similarity transformation. We evaluate our algorithm to determine which of its novel aspects improve AAM fitting performance.

Keyphrases

active appearance model    appearance variation    related concept    aam fitting performance    nonlinear parametric model    input image    pixel intensity    active blob    model instance    generative model    novel aspect    inverse compositional image alignment algorithm    efficient fitting algorithm    similarity transformation    nonlinear optimization problem    morphable model    certain visual phenomenon   

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