We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Three techniques: Principal Component Analy...
In this paper, we propose an ICA(Indepdendent Component Analysis) based face recognition algorithm, which is robust to illumination and pose variation. Generally, it is well known...
Tae-Kyun Kim, Hyunwoo Kim, Wonjun Hwang, Seok-Cheo...
In this paper, we consider the problem of automatically detecting a facial symmetry axis in what we will call a standard human face image (acquired when the subject is looking dir...
VIMS Lab is situated in Department of Computer & Information Sc, University of Delaware, Newark, DE. USA.
At VIMS we work on various problems related to image/video processing...
In the past decade or so, subspace methods have been largely used in face recognition ? generally with quite success. Subspace approaches, however, generally assume the training d...