Face Detection and Modeling for Recognition - Biometrics Research ...
Face Detection and Modeling for Recognition - Biometrics Research ...
Face Detection and Modeling for Recognition - Biometrics Research ...
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can be applied to a 3D face model whenever a facial component is coarsely<br />
relocated or is finely de<strong>for</strong>med by the 2.5D snake.<br />
In the second face modeling method, we developed a technique <strong>for</strong> face alignment:<br />
• Interacting snakes: The snake de<strong>for</strong>mation is <strong>for</strong>mulated by a finite difference<br />
approach. The initial snakes <strong>for</strong> facial components are obtained from the<br />
2D projection of the semantic face graph on a generic 3D face model. We have<br />
designed the interacting snakes technique <strong>for</strong> manipulating multiple snakes iteratively<br />
that minimizes the attraction energy functionals on both contours<br />
<strong>and</strong> enclosed regions of individual snakes <strong>and</strong> minimizes the repulsion energy<br />
functionals among multiple snakes.<br />
1.12.<br />
In face recognition, we have proposed two paradigms as shown in Figs. 1.11 <strong>and</strong><br />
• The first (range data-based) recognition paradigm: This paradigm is designed<br />
to automate <strong>and</strong> augment appearance-based face recognition approaches<br />
based on 3D face models. In this system, we have integrated our face detection<br />
algorithm, face modeling method using the 2.5D snake, <strong>and</strong> an appearancebased<br />
recognition method using the hierarchical discriminant regression [78].<br />
However, the recognition module can be replaced with other appearance-based<br />
algorithms such as PCA-based <strong>and</strong> LDA-based methods. The system can learn<br />
a 3D face model <strong>for</strong> an individual, <strong>and</strong> generate an arbitrary number of 2D<br />
face images under different head poses <strong>and</strong> illuminations (can be extended to<br />
different expressions) <strong>for</strong> training an appearance-based face classifier.<br />
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