The inter-frame information for analyzing human face movement manifold is modeled by the statistical shape theory. Using the Riemannian geometry principles, we map a sequence of face shapes to a unified tangent space and obtain a curve corresponding to the face movement. The experimental results show that the face movement sequence forms a trajectory in a complex tangent space. Furthermore, the extent and type of face expression could be depicted as the range and direction of the curve. This represents a novel approach for face movement classification using shape-based analysis.
- Face movement
- Manifold learning
- Statistical shape theory
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics