Abstract
We focus on the problem of developing a coupled statistical model that can be used to recover surface height from brightness images of faces. The idea is to couple intensity and height by jointly modeling their combined variations. The models are constructed by performing Principal Component Analysis (PCA) on the shape coefficients for both intensity and height training data. By fitting the model to intensity data, the height information is implicitly recovered from the coupled shape parameters. Experiments show that the methods generate accurate surfaces from out-of training intensity images.
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Castelán, M., Smith, W.A.P., Hancock, E.R. (2006). A Coupled Statistical Model for Face Shape Recovery. In: Yeung, DY., Kwok, J.T., Fred, A., Roli, F., de Ridder, D. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2006. Lecture Notes in Computer Science, vol 4109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11815921_99
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DOI: https://doi.org/10.1007/11815921_99
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