Close
Metadata

%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2012/07.09.15.07
%2 sid.inpe.br/sibgrapi/2012/07.09.15.07.49
%T Computing gender difference using Fisher-Rao metric from facial surface normals
%D 2012
%A Ceolin, Simone Regina,
%A Hancock, Edwin R.,
%@affiliation Centro Universitário Franciscano
%@affiliation University of York
%E Freitas, Carla Maria Dal Sasso,
%E Sarkar, Sudeep,
%E Scopigno, Roberto,
%E Silva, Luciano,
%B Conference on Graphics, Patterns and Images, 25 (SIBGRAPI)
%C Ouro Preto
%8 Aug. 22-25, 2012
%S Proceedings
%I IEEE Computer Society
%J Los Alamitos
%K Fisher-Rao metric, surface normal, shape-from-shading.
%X 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.
%@language en
%3 paper_sibgrapi_2012.pdf


Close