Visible and Infrared Face Identification via Sparse Representation
Résumé
We present a facial recognition technique based on facial sparse representation. A dictionary is learned from data, and patches extracted from a face are decomposed in a sparse manner onto this dictionary. We particularly focus on the design of dictionaries that play a crucial role in the final identification rates. Applied to various databases and modalities, we show that this approach gives interesting performances. We propose also a score fusion framework that allows quantifying the saliency classifiers outputs and merging them according to these saliencies.
Domaines
Traitement des images [eess.IV]
Origine : Fichiers éditeurs autorisés sur une archive ouverte
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