Abstract
3D Morphable Face Models (3DMM) have been used in face recognition for some time now. They can be applied in their own right as a basis for 3D face recognition and analysis involving 3D face data. However their prevalent use over the last decade has been as a versatile tool in 2D face recognition to normalise pose, illumination and expression of 2D face images. A 3DMM has the generative capacity to augment the training and test databases for various 2D face processing related tasks. It can be used to expand the gallery set for pose-invariant face matching. For any 2D face image it can furnish complementary information, in terms of its 3D face shape and texture. It can also aid multiple frame fusion by providing the means of registering a set of 2D images. A key enabling technology for this versatility is 3D face model to 2D face image fitting. In this paper recent developments in 3D face modelling and model fitting will be overviewed, and their merits in the context of diverse applications illustrated on several examples, including pose and illumination invariant face recognition, and 3D face reconstruction from video.
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Kittler, J., Huber, P., Feng, ZH., Hu, G., Christmas, W. (2016). 3D Morphable Face Models and Their Applications. In: Perales, F., Kittler, J. (eds) Articulated Motion and Deformable Objects. AMDO 2016. Lecture Notes in Computer Science(), vol 9756. Springer, Cham. https://doi.org/10.1007/978-3-319-41778-3_19
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