TY - GEN
T1 - Explicit occlusion detection based deformable fitting for facial landmark localization
AU - Yu, Xiang
AU - Yang, Fei
AU - Huang, Junzhou
AU - Metaxas, Dimitris N.
PY - 2013
Y1 - 2013
N2 - This paper addresses the problem of facial landmark localization on partially occluded faces. We proposes an explicit occlusion detection based deformable fitting model for occluded landmark localization. Most recent shape registration methods apply landmark local search and attempt to simultaneously minimize both the model error and localization error. However, if part of the shape is occluded, those methods may lead to misalignment. In this paper, we introduce regression based occlusion detection to restrict the occluded landmarks' error propagation from passing to the overall optimization. Assuming the parameter model being Gaussian, we propose a weighted deformable fitting algorithm that iteratively approaches the optima. Experimental results in our synthesized facial occlusion database demonstrate the advantage of our method.
AB - This paper addresses the problem of facial landmark localization on partially occluded faces. We proposes an explicit occlusion detection based deformable fitting model for occluded landmark localization. Most recent shape registration methods apply landmark local search and attempt to simultaneously minimize both the model error and localization error. However, if part of the shape is occluded, those methods may lead to misalignment. In this paper, we introduce regression based occlusion detection to restrict the occluded landmarks' error propagation from passing to the overall optimization. Assuming the parameter model being Gaussian, we propose a weighted deformable fitting algorithm that iteratively approaches the optima. Experimental results in our synthesized facial occlusion database demonstrate the advantage of our method.
UR - http://www.scopus.com/inward/record.url?scp=84881531161&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881531161&partnerID=8YFLogxK
U2 - 10.1109/FG.2013.6553723
DO - 10.1109/FG.2013.6553723
M3 - Conference contribution
AN - SCOPUS:84881531161
SN - 9781467355452
T3 - 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2013
BT - 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2013
T2 - 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2013
Y2 - 22 April 2013 through 26 April 2013
ER -