TY  - CONF
AU  - Bogdan Raducanu
AU  - Fadi Dornaika
A2  - ECCVW
PY  - 2012//
TI  - Pose-Invariant Face Recognition in Videos for Human-Machine Interaction
T2  - LNCS
BT  - 12th European Conference on Computer Vision
SP  - 566.575
VL  - 7584
PB  - Springer Berlin Heidelberg
N2  - Human-machine interaction is a hot topic nowadays in the communities of computer vision and robotics. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. This is mostly due to the difficulty of simultaneously handling variations in illumination, pose, and occlusions. In this paper, we propose a novel approach for robust pose-invariant face recognition for human-robot interaction based on the real-time fitting of a 3D deformable model to input images taken from video sequences. More concrete, our approach generates a rectified face image irrespective with the actual head-pose orientation. Experimental results performed on Honda video database, using several manifold learning techniques, show a distinct advantage of the proposed method over the standard 2D appearance-based snapshot approach.
SN  - 0302-9743
SN  - 978-3-642-33867-0
L1  - http://refbase.cvc.uab.es/files/RaD2012e.pdf
UR  - http://dx.doi.org/10.1007/978-3-642-33868-7_56
N1  - OR;MV
ID  - Bogdan Raducanu2012
ER  -