A novel method for post-surgery face recognition using sum of facial parts recognition

Plastic surgery is becoming more and more commonplace today due to its increasing acceptance in society and its cost-affordability. This in turn has led to the need for developing highly accurate post-surgery face recognition techniques, a problem space which differs significantly from traditional face recognition. In this paper we first conduct a statistical study to show that facial plastic surgery operations correlate with a desire to conform to a golden ratio with respect to the human face. We then apply this knowledge, with the notion of considering a face in terms of the sum of its parts, to propose a novel face recognition technique. The proposed technique is then evaluated against well known datasets, and as per our experiments achieves a recognition rate of 85.35%, which significantly outperforms other state of the art techniques.