Face Recognition System Invariant to Light-Camera Setup

摘要

This paper proposes an efficient face recognition system where images are acquired under different camera positions and lighting conditions. Active Appearance model is used to obtain shape and appearance information from faces in the form of feature vectors. Bilinear model then works upon these vectors to obtain style specific basis matrices in the training phase. In the test phase the bilinear model uses elastic net regularization to determine stable content vectors using style specific basis matrix. Euclidean distance between content vectors of two images is used to take decision on matching. The proposed system has been tested on 1255 images of 108 subjects. Experiment results reveal that the system achieves an accuracy of 95% when five top best matches are considered in a closed set identification setup.