This paper
introduces plastic surgery as a new dimension for face recognition
algorithms. We present an experimental study to quantitatively evaluate
the performance of face recognition algorithms on a plastic
surgery database that contains face images with both local and global
surgeries. The study shows that appearance, feature, and texture based
algorithms are unable to effectively mitigate the variations caused
by the plastic surgery procedures. Based on the results, we believe
that more research is required in order to design an optimal face
recognition algorithm that can also account for the challenges due
to plastic surgery. It is our assertion that the results of this work
would inspire further research in this important area.