Abstract
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.
Original language | English |
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Article number | 037004 |
Journal | Optical Engineering |
Volume | 51 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2012 Mar |
Externally published | Yes |
Keywords
- Face movement
- Manifold learning
- Statistical shape theory
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Engineering(all)