Title :
Statistical Analysis of 3D Faces in Motion
Author :
Bolkart, Timo ; Wuhrer, Stefanie
Author_Institution :
Cluster of Excellence MMCI, Saarland Univ., Saarbrucken, Germany
fDate :
June 29 2013-July 1 2013
Abstract :
We perform statistical analysis of 3D facial shapes in motion over different subjects and different motion sequences. For this, we represent each motion sequence in a multilinear model space using one vector of coefficients for identity and one high-dimensional curve for the motion. We apply the resulting statistical model to two applications: to synthesize motion sequences, and to perform expression recognition. En route to building the model, we present a fully automatic approach to register 3D facial motion data, Based on a multilinear model, and show that the resulting registrations are of high quality.
Keywords :
face recognition; gesture recognition; image motion analysis; image registration; image sequences; shape recognition; statistical analysis; stereo image processing; 3D facial motion data registration; 3D facial shape; coefficient vector; expression recognition; high-dimensional curve; motion sequence synthesis; multilinear model space; statistical analysis; statistical model; Computational modeling; Data models; Databases; Shape; Statistical analysis; Three-dimensional displays; Training data;
Conference_Titel :
3D Vision - 3DV 2013, 2013 International Conference on
Conference_Location :
Seattle, WA
DOI :
10.1109/3DV.2013.22