A coupled statistical model for face shape recovery from brightness images.
We focus on the problem of developing a coupled statistical model that can be used to recover facial shape from brightness images of faces. We study three alternative representations for facial shape. These are the surface height function, the surface gradient, and a Fourier basis representation. We jointly capture variations in intensity and the surface shape representations using a coupled statistical model. The model is constructed by performing principal components analysis on sets of parameters describing the contents of the intensity images and the facial shape representations. By fitting the coupled model to intensity data, facial shape is implicitly recovered from the shape parameters. Experiments show that the coupled model is able to generate accurate shape from out-of-training-sample intensity images.
Castelán
Mario
M
Department of Computer Science, University of York, York YO1 5DD, UK. mario@cs.york.ac.uk
Smith
William A P
WA
Hancock
Edwin R
ER
D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods; D003198:Computer Simulation; D005145:Face / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008029:Lighting / Q000379:methods; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D010783:Photometry / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity