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http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/480| Face image synthesis and interpretation using 3D illumination-based active appearance models | |
| SALVADOR EUGENIO AYALA RAGGI | |
| LEOPOLDO ALTAMIRANO ROBLES | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| Computer vision Pattern recognition Face recognition | |
| This work presents an innovative and fast approach for face interpretation invariant to lighting and pose. The presented approach called 3D-IAAM (3D Illumination-Based Active Appearance Model) performs interpretation by fitting a parametric 3D face model to an input image using an optimization algorithm. The parameters obtained after the fitting process describe the appearance of the face. The fitting process is automatic and only requires a 2D position and a scale factor as initialization. The proposed model is a natural 3D extension of active appearance models and is based on modeling, separately and simultaneously, 3D pose, 3D shape, albedo, and lighting. 3D-IAAM is capable of synthesizing faces with arbitrary 3D shape, 3D pose, albedo and lighting. In order to fit the model to an input image, a fast optimization algorithm able to fit face images with non-uniform lighting and arbitrary pose is proposed in this thesis. The proposed fitting algorithm, based on a gradient descent approach, executes a fast update to the Jacobian by using the lighting parameters estimated in each iteration of the fitting process. The optimization method is able to accurately estimate the parameters of 3D shape and albedo, which are strongly related to identity. Experimental results, suggest that our model can be extended to face recognition under non-uniform lighting and variable pose. Them a in contribution of this thesis is the novel method for face interpretation 3D-IAAM based on analysis by synthesis. The particular contributions derived from this work are: 1. A method for constructing 3D face models from surface meshes estimated by photometric stereo. 2. A deformable model capable of synthesizing face images with arbitrary pose, shape, albedo and lighting. Our face synthesis algorithm can arbitrarily create face images with multiple identities, 3D pose and lighting by varying the value of a compact set of parameters. 3. A novel way to normalize the albedo in terms of illumination parameters. The albedo normalization is applied over an image normalized in pose and shape which has been sampled from the original test image. This normalized face image is used during the fitting process in order to be compared with are reference mean face image which evolves in lighting according to the illumination parameters estimated in each iteration. | |
| Instituto Nacional de Astrofísica, Óptica y Electrónica | |
| 2010-02 | |
| Tesis de doctorado | |
| Inglés | |
| Estudiantes Investigadores Público en general | |
| Ayala-Raggi S.E. | |
| CIENCIA DE LOS ORDENADORES | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | Doctorado en Ciencias Computacionales |
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| AyalaRaSE.pdf | 10.83 MB | Adobe PDF | Visualizar/Abrir |