Abstract

The system presented here is a specialized version of a general object recognition system. Images of faces are represented as graphs, labeled with topographical information and local templates. Different poses are represented by different graphs. New graphs of faces are generated by an elastic graph matching procedure comparing the new face with a set of precomputed graphs: the "general face knowledge". The final phase of the matching process can be used to generate composite images of faces and to determine certain features represented in the general face knowledge, such as gender or the presence of glasses or a beard. The graphs can be compared by a similarity function which makes the system efficient in recognizing faces. 1 Introduction Face recognition systems can be subdivided into two main categories [1] depending on the nature of the coding of an input picture and its processing. Schemes that use pixels (grey-level values) as the basis for their coding and various forms of sta...

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