Robust Face Recognition after Plastic Surgery Using Local Region Analysis

Face recognition in real-world applications is often hindered by uncontrolled settings including pose, expression, and illumination changes, and/or ageing. Additional challenges related to changes in facial appearance due to plastic surgery have become apparent recently. We exploit the fact that plastic surgery bears on appearance in a non-uniform fashion using a recognition approach that integrates information derived from local region analysis. We implemented and evaluated the performance of two new integrative methods, FARO and FACE, which are based on fractals and a localized version of a correlation index, respectively Experimental results confirm the expectation that face recognition is indeed challenged by the effects of plastic surgery. The same experimental results also show that both FARO and FACE compare favourably against standard face recognition methods such as PCA and LDA.