2012 25th SIBGRAPI Conference on Graphics, Patterns and Images (2012)
Ouro Preto, Brazil Brazil
Aug. 22, 2012 to Aug. 25, 2012
The aim in this paper is to explore whether the Fisher-Rao metric can be used to characterise the shape changes due to gender difference. We work using a 2.5D representation based on facial surface normals (or facial needle-maps) for gender classification. The needle-map is a shape representation which can be acquired from 2D intensity images using shape-from-shading (SFS). Using the von-Mises Fisher distribution, we compute the elements of the Fisher information matrix, and use this to compute geodesic distance between fields of surface normals to construct a shape-space. We embed the fields of facial surface normals into a low dimensional pattern space using a number of alternative methods including multidimensional scaling, heat kernel embedding and commute time embedding. We present results on clustering the embedded faces using the Max Planck and EAR database.
Shape, Vectors, Measurement, Manifolds, Surface treatment, Principal component analysis, Electronics packaging, shape-from-shading, Fisher-Rao metric, surface normal
S. R. Ceolin and E. R. Hancock, "Computing Gender Difference Using Fisher-Rao Metric from Facial Surface Normals," 2012 25th SIBGRAPI Conference on Graphics, Patterns and Images(SIBGRAPI), Ouro Preto, Brazil Brazil, 2012, pp. 336-343.