Facial biometry by stimulating salient singularity masks
We present a novel approach for face recognition based on salient singularity descriptors. The automatic feature extraction is performed thanks to a salient point detector, and the singularity information selection is performed by a SOM region-based structuring. The spatial singularity distribution is preserved in order to activate specific neuron maps and the local salient signature stimuli reveals the individual identity. This proposed method appears to be particularly robust to facial expressions and facial poses, as demonstrated in various experiments on well-known databases.