Title :
Modelling the variability in face images
Author :
Edwards, G.J. ; Lanitis, A. ; Taylor, C.J. ; Cootes, T.F.
Author_Institution :
Dept. of Med. Biophys., Manchester Univ., UK
Abstract :
Model based approaches to the interpretation of face images have proved very successful. We have previously described statistically based models of face shape and grey-level appearance and shown how they can be used to perform various coding and interpretation tasks (Lanitis et al., 1995). In the paper we describe improved methods of modelling, which couple shape and grey-level information more directly than our existing methods, isolate the changes in appearance due to different sources of variability (person, expression, pose, lighting) and deal with nonlinear shape variation. We show that the new methods are better suited to interpretation and tracking tasks
Keywords :
computational geometry; face recognition; image coding; image recognition; statistical analysis; expression; face image recognition; face image variability modelling; face shape; grey-level appearance; image coding; image interpretation; lighting; model based approaches; nonlinear shape variation; person; pose; statistical models; tracking tasks; Anatomical structure; Biomedical imaging; Biophysics; Deformable models; Image coding; Image generation; Image reconstruction; Optical coupling; Shape; Statistical analysis;
Conference_Titel :
Automatic Face and Gesture Recognition, 1996., Proceedings of the Second International Conference on
Conference_Location :
Killington, VT
Print_ISBN :
0-8186-7713-9
DOI :
10.1109/AFGR.1996.557286
