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We present a regression-based scheme for multi-view facial expression recognition based on 2D geometric features. We address the problem by mapping facial points (e.g. mouth corners) from non-frontal to frontal view where further recognition of the expressions can be performed using a state-of-the-art facial expression recognition method. To learn the mapping functions we investigate four regression...
This study investigates a new direction of characterising 3D face based on Gaussian curvature for classification problems. This method relies on the geometric facial models regarding as input information. Within a sub-surface we define, which includes much invariant over facial expressions changing, symmetry characteristic is evaluated combining with the study of two distinguishing profiles based...
This paper address new face verification scheme based on Log-Gabor filter (texture based) and Gaussian Mixture Model. The proposed method consists of three parts. The first part is a Log-Gabor filtering on facial image. The second part is to model the Log-Gabor filter response using Gaussian Mixture Model to obtain more than one set of features. The third part is transforming the set of features using...
This work is framed in the field of statistical face analysis. In particular, the problem of accurate segmentation of prominent features of the face in frontal view images is addressed. We propose a method that generalizes linear active shape models (ASMs)l which have already been used for this task. The technique is built upon the development of a nonlinear intensity model, incorporating a reduced...
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