TY - JOUR
T1 - Statistical shape analysis for face movement manifold modeling
AU - Wang, Xiaokan
AU - Mao, Xia
AU - Caleanu, Catalin Daniel
AU - Ishizuka, Mitsuru
PY - 2012/3
Y1 - 2012/3
N2 - 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.
AB - 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.
KW - Face movement
KW - Manifold learning
KW - Statistical shape theory
UR - http://www.scopus.com/inward/record.url?scp=84891775360&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891775360&partnerID=8YFLogxK
U2 - 10.1117/1.OE.51.3.037004
DO - 10.1117/1.OE.51.3.037004
M3 - Article
AN - SCOPUS:84891775360
SN - 0091-3286
VL - 51
JO - Optical Engineering
JF - Optical Engineering
IS - 3
M1 - 037004
ER -