Title :
Deformable face ensemble alignment with robust grouped-L1 anchors
Author :
Xin Cheng ; Fookes, Clinton ; Sridharan, Sridha ; Saragih, Jason ; Lucey, Simon
Author_Institution :
Queensland Univ. of Technol., Brisbane, QLD, Australia
Abstract :
Many methods exist at the moment for deformable face fitting. A drawback to nearly all these approaches is that they are (i) noisy in terms of landmark positions, and (ii) the noise is biased across frames (i.e. the misalignment is toward common directions across all frames). In this paper we propose a grouped L1-norm anchored method for simultaneously aligning an ensemble of deformable face images stemming from the same subject, given noisy heterogeneous landmark estimates. Impressive alignment performance improvement and refinement is obtained using very weak initialization as “anchors”.
Keywords :
face recognition; alignment performance improvement; deformable face ensemble alignment; grouped L1-norm anchored method; landmark positions; noisy heterogeneous landmark; Active appearance model; Databases; Face; Noise measurement; Robustness; Shape; Vectors;
Conference_Titel :
Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-5545-2
Electronic_ISBN :
978-1-4673-5544-5
DOI :
10.1109/FG.2013.6553739