3d face representation and recognition using spherical harmonics

Tunçer, Fahri
In this study, a 3D face representation and recognition method based on spherical harmonics expansion is proposed. The input data to the method is range image of the face. This data is called 2.5 dimensional. Input faces are manually marked on the two eyes, nose and chin points. In two dimensions, using the marker points, the human face is modeled as two concentric half ellipses for the selection of region of interest. These marker points are also used in three dimensions to register the faces so that the nose point tip is at the origin and the line across the two eyes lies parallel to the horizontal plane. A PCA based component analysis is done to further align the faces vertically. The aligned face is stitched and mapped to an ellipsoid and transformed using real spherical harmonics expansion. The real harmonics expansion coefficients are labeled and stored into a gallery. Using these coefficients as input, several classification algorithms are applied and the results are reported.


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3D object recognition is performed using a scale and orientation invariant feature extraction method and a scale and orientation invariant topological representation. 3D surfaces are represented by sparse, repeatable, informative and semantically meaningful 3D surface structures, which are called multiscale features. These features are extracted with their scale (metric size and resolution) using the classified scale-space of 3D surface curvatures. Triplets of these features are used to represent the surfac...
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Akagündüz, Erdem; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2011)
In this thesis, a generic, scale and resolution invariant method to extract 3D features from 3D surfaces, is proposed. Features are extracted with their scale (metric size and resolution) from range images using scale-space of 3D surface curvatures. Different from previous scale-space approaches; connected components within the classified curvature scale-space are extracted as features. Furthermore, scales of features are extracted invariant of the metric size or the sampling of the range images. Geometric ...
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Citation Formats
F. Tunçer, “3d face representation and recognition using spherical harmonics,” Ph.D. - Doctoral Program, Middle East Technical University, 2008.