2007 IEEE 11th International Conference on Computer Vision 2007
DOI: 10.1109/iccv.2007.4409185
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Bilinear Active Appearance Models

Abstract: Appearance Models have been applied to model the space of human faces over the last two decades. In particular, Active Appearance Models (AAMs) have been successfully used for face tracking, synthesis and recognition, and they are one of the state-of-the-art approaches due to its efficiency and representational power. Although widely employed, AAMs suffer from a few drawbacks, such as the inability to isolate pose, identity and expression changes. This paper proposes Bilinear Active Appearance Models (BAAMs), … Show more

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Cited by 27 publications
(20 citation statements)
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“…AAM can warp the initial shape and appearance into the current face very well due to both of its shape constraint and appearance constraint. There are also many methods based on them, like multi-view ASM [3], CLM [4], bilinear AAM [5] and tensor-based AAM [6]. Since these methods are parametric models, it is hard to avoid a suboptimization problem.…”
Section: Cascaded Regression To Face Alignmentmentioning
confidence: 99%
See 1 more Smart Citation
“…AAM can warp the initial shape and appearance into the current face very well due to both of its shape constraint and appearance constraint. There are also many methods based on them, like multi-view ASM [3], CLM [4], bilinear AAM [5] and tensor-based AAM [6]. Since these methods are parametric models, it is hard to avoid a suboptimization problem.…”
Section: Cascaded Regression To Face Alignmentmentioning
confidence: 99%
“…Typical generative models include Active Shape Model (ASM) [1], Active Appearance Model (AAM) [2], and their extensions [3][4][5][6]. In this type of methods, the optimization target is model parameters.…”
Section: Introductionmentioning
confidence: 99%
“…Typical generative models including active shape models [2], active appearance models [3], and their extensions [4][5][6] mitigate the influence of illumination and pose, but tend to fail when used in the wild. Recently, discriminative models have shown promising performance for robust facial landmark detection, represented by cascaded regression-based methods, e.g., explicit shape regression [7], and the supervised descent method [8].…”
Section: Introductionmentioning
confidence: 99%
“…Typical generative models are ASM [4], AAM [5] and their extensions [3], [6], [7], [39], [43], [44]. A common characteristic of ASM and AAM is a parametric PCA-based shape model that is constrained by the corresponding eigenvalues when fitting the models to an input image.…”
Section: A Generative Modelsmentioning
confidence: 99%