TY - GEN
T1 - Robust shape-based head tracking
AU - Hou, Yunshu
AU - Sahli, Hichem
AU - Ilse, Ravyse
AU - Zhang, Yanning
AU - Zhao, Rongchun
PY - 2007
Y1 - 2007
N2 - This work presents a new method to automatically locate frontal facial feature points under large scene variations (illumination, pose and facial expressions). First, we use a kernel-based tracker to detect and track the facial region in an image sequence. Then the results of the face tracking, i.e. face region and face pose, are used to constrain prominent facial feature detection and tracking. In our case, eyes and mouth corners are considered as prominent facial features. In a final step, we propose an improvement to the Bayesian Tangent Shape Model for the detection and tracking of the full shape model. A constrained regularization algorithm is proposed using the head pose and the accurately aligned prominent features to constrain the deformation parameters of the shape model. Extensive experiments demonstrate the accuracy and effectiveness of our proposed method.
AB - This work presents a new method to automatically locate frontal facial feature points under large scene variations (illumination, pose and facial expressions). First, we use a kernel-based tracker to detect and track the facial region in an image sequence. Then the results of the face tracking, i.e. face region and face pose, are used to constrain prominent facial feature detection and tracking. In our case, eyes and mouth corners are considered as prominent facial features. In a final step, we propose an improvement to the Bayesian Tangent Shape Model for the detection and tracking of the full shape model. A constrained regularization algorithm is proposed using the head pose and the accurately aligned prominent features to constrain the deformation parameters of the shape model. Extensive experiments demonstrate the accuracy and effectiveness of our proposed method.
UR - http://www.scopus.com/inward/record.url?scp=38149010400&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-74607-2_31
DO - 10.1007/978-3-540-74607-2_31
M3 - 会议稿件
AN - SCOPUS:38149010400
SN - 9783540746065
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 340
EP - 351
BT - Advanced Concepts for Intelligent Vision Systems - 9th International Conference, ACIVS 2007, Proceedings
PB - Springer Verlag
T2 - 9th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2007
Y2 - 28 August 2007 through 31 August 2007
ER -