In this paper we propose a real time face recognition method that combines face matching and identity verification modules in a feedback loop, exploiting the temporal efficiency of matching and the performances of SVM classifiers. Our approach represents an ad-hoc solution for settings characterized by variable quantity, quality and distribution of labeled data among the identities. We assess the procedure on two data sets of different complexities, showing the effectiveness of our solution. For its intrinsic peculiarities and its limited computational cost the method finds application in real time systems, and will be implemented on a wearable device for supporting visually impaired people to localize known faces.
Combining retrieval and classification for real-time face recognition
FUSCO, GIOVANNI;NOCETI, NICOLETTA;ODONE, FRANCESCA
2012-01-01
Abstract
In this paper we propose a real time face recognition method that combines face matching and identity verification modules in a feedback loop, exploiting the temporal efficiency of matching and the performances of SVM classifiers. Our approach represents an ad-hoc solution for settings characterized by variable quantity, quality and distribution of labeled data among the identities. We assess the procedure on two data sets of different complexities, showing the effectiveness of our solution. For its intrinsic peculiarities and its limited computational cost the method finds application in real time systems, and will be implemented on a wearable device for supporting visually impaired people to localize known faces.
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