Fifth International Conference on Computer Vision (ICCV'95) A unified approach to coding and interpreting face images Massachusetts Institute of Technology, Cambridge, Massachusetts June 20-June 23 ISBN: 0-8186-7042-8
Face images are difficult to interpret because they are highly variable. Sources of variability include individual appearance, 3D pose, facial expression and lighting. We describe a compact parametrised model of facial appearance which takes into account all these sources of variability. The model represents both shape and grey-level appearance and is created by performing a statistical analysis over a training set of face images. A robust multi-resolution search algorithm is used to fit the model to faces in new images. This allows the main facial features to be located and a set of shape and grey-level appearance parameters to be recovered. A good approximation to a given face can be reconstructed using less than 100 of these parameters. This representation can be used for tasks such as image coding, person identification, pose recovery, gender recognition and expression recognition. The system performs well on all the tasks listed above.
Index Terms:
face recognition; image recognition; lighting; statistical analysis; search problems; image reconstruction; image coding; face image interpretation; image coding; variability; 3D pose; facial expression; lighting; facial appearance; grey-level appearance; statistical analysis; multi-resolution search algorithm; face reconstruction; person identification; pose recovery; gender recognition; expression recognition
Citation:
A. Lanitis, C.J. Taylor, T.F. Cootes, "A unified approach to coding and interpreting face images," iccv, pp.368, Fifth International Conference on Computer Vision (ICCV'95), 1995 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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