TY - GEN
T1 - Expressive Maps for 3D Facial Expression Recognition
AU - Ocegueda, Omar
AU - Fang, Tianhong
AU - Shah, Shishir K.
AU - Kakadiaris, Ioannis A.
PY - 2011
Y1 - 2011
N2 - We present a semi-automatic 3D Facial Expression Recognition system based on geometric facial information. In this approach the 3D facial meshes are first fitted to an Annotated Face Model (AFM). Then the Expressive Maps are computed which indicate the parts of the face that are most expressive according to a particular geometric feature (e.g. vertex coordinates normals and local curvature). The Expressive Maps provide a way to analyze the geometric features in terms of their discriminative information and their distribution along the face and allow the reduction of the dimensionality of the input space to 2:5% of the original size. Using the selected features a simple linear classifier was trained and yielded a very competitive average recognition rate of 90:4% when evaluated using ten-fold cross validation on the publicly available BU-3DFE database.
AB - We present a semi-automatic 3D Facial Expression Recognition system based on geometric facial information. In this approach the 3D facial meshes are first fitted to an Annotated Face Model (AFM). Then the Expressive Maps are computed which indicate the parts of the face that are most expressive according to a particular geometric feature (e.g. vertex coordinates normals and local curvature). The Expressive Maps provide a way to analyze the geometric features in terms of their discriminative information and their distribution along the face and allow the reduction of the dimensionality of the input space to 2:5% of the original size. Using the selected features a simple linear classifier was trained and yielded a very competitive average recognition rate of 90:4% when evaluated using ten-fold cross validation on the publicly available BU-3DFE database.
UR - http://www.scopus.com/inward/record.url?scp=84856645312&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84856645312&partnerID=8YFLogxK
U2 - 10.1109/ICCVW.2011.6130397
DO - 10.1109/ICCVW.2011.6130397
M3 - Conference contribution
AN - SCOPUS:84856645312
SN - 9781467300629
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 1270
EP - 1275
BT - 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
T2 - 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011
Y2 - 6 November 2011 through 13 November 2011
ER -