3D-Aided Face Recognition Robust to Expression and Pose Variations

Baptiste Chu, Sami Romdhani, Liming Chen
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
Expression and pose variations are major challenges for reliable face recognition (FR) in 2D. In this paper, we aim to endow state of the art face recognition SDKs with robustness to simultaneous facial expression variations and pose changes by using an extended 3D Morphable Model (3DMM) which isolates identity variations from those due to facial expressions. Specifically, given a probe with expression, a novel view of the face is generated where the pose is rectified and the expression
more » ... zed. We present two methods of expression neutralization. The first one uses prior knowledge to infer the neutral expression image from an input image. The second method, specifically designed for verification, is based on the transfer of the gallery face expression to the probe. Experiments using rectified and neutralized view with a standard commercial FR SDK on two 2D face databases, namely Multi-PIE and AR, show significant performance improvement of the commercial SDK to deal with expression and pose variations and demonstrates the effectiveness of the proposed approach.
doi:10.1109/cvpr.2014.245 dblp:conf/cvpr/ChuRC14 fatcat:cy37guf4ybal5olerdgzx675ve