TY - GEN
T1 - AAM fitting using shape parameter distribution
AU - Shiraishi, Youhei
AU - Fujie, Shinya
AU - Kobayashi, Tetsunori
PY - 2012
Y1 - 2012
N2 - A novel constraint using shape parameter distribution into the AAM fitting method is proposed. Active appearance models (AAMs) are some of the most popular facial models. AAM-based face tracking delivers accurate alignment results. However, non-face-like shapes can also be estimated by AAMs, unlike by the conventional AAM fitting method, which only minimizes the matching error of the image. This is one of the causes for face tracking performance degradation in AAMs. A constraint using the shape parameter distribution is added in order to solve this problem.
AB - A novel constraint using shape parameter distribution into the AAM fitting method is proposed. Active appearance models (AAMs) are some of the most popular facial models. AAM-based face tracking delivers accurate alignment results. However, non-face-like shapes can also be estimated by AAMs, unlike by the conventional AAM fitting method, which only minimizes the matching error of the image. This is one of the causes for face tracking performance degradation in AAMs. A constraint using the shape parameter distribution is added in order to solve this problem.
KW - Active appearance models
KW - Face tracking
KW - Inverse compositional image alignment
UR - http://www.scopus.com/inward/record.url?scp=84869795664&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84869795664&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84869795664
SN - 9781467310680
T3 - European Signal Processing Conference
SP - 2238
EP - 2242
BT - Proceedings of the 20th European Signal Processing Conference, EUSIPCO 2012
T2 - 20th European Signal Processing Conference, EUSIPCO 2012
Y2 - 27 August 2012 through 31 August 2012
ER -