Face Joint Alignment Using Local Method
Gang Zhang, Tang Sikan, Lian Qiang Niu · 2016
It is an under-determined problem that local methods are used for face alignment of an image, although good results can be obtained by using an auxiliary model or a priori information.In comparison, joint alignment using multiple face images of the same person has more advantages.In this paper, the rectangle round a face is acquired, and then logistic regressors are used to obtain the candidates of the regions round the landmark points.The non-parametric face shape models are used to constrain the configuration among the regions.On this basis, Generalized Procrustes Analysis is used for rigid joint alignment.Tests are carried out on LFW dataset, and the results show that joint alignment will cause overall drifting, and but helpful for facial landmark alignment in outer contour.