Abstract
In this work, we propose a 2D-PCA based face recognizer as a semi-automatic tool for helping indexing people in historical photographs. In the proposed recognizer we cope with the scarcity of training samples and the lack of precision of the detector using a training scheme in two stages. The first stage uses an external face database to compute an average face that is used as a reference either at the second training stage and at the recognition step. We also added an auxiliary distance measure we call relative distance to reorder the results generated by the original Euclidean-based distance measure for 2D-PCA. Experimental results with the ORL database as the external face database and a real collection of historical photographs have shown the viability of the proposed tool. These experiments also indicated that both improvements proposed were indeed able to increase recognition rates.
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