We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
The work presented in this paper is an extension of our two previous works [1, 2]. In the first paper [1], we proposed a low dimensional feature (i-vectors) extractor which is su...
Mohammed Senoussaoui, Patrick Kenny, Pierre Dumouc...
We present a systematic procedure for selecting facial fiducial points associated with diverse structural characteristics of a human face. We identify such characteristics from th...
Shalini Gupta, J. K. Aggarwal, Mia K. Markey, Alan...
By representing images and image prototypes by linear subspaces spanned by "tangent vectors" (derivatives of an image with respect to translation, rotation, etc.), impre...
Nebojsa Jojic, Patrice Simard, Brendan J. Frey, Da...
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...