A Case Study on Unconstrained Facial Recognition Using the Boston Marathon Bombings Suspects

The investigation surrounding the Boston Marathon bombings was a missed opportunity for automated facial recognition to assist law enforcement in identifying suspects. We simulate the identification scenario presented by the investigation using two state-of-the-art commercial face recognition systems, and gauge the maturity of face recognition technology in matching low quality face images of uncooperative subjects. Our experimental results show one instance where a commercial face matcher returns a rank-one hit for suspect Dzhokhar Tsarnaev against a one million mugshot background database. Though issues surrounding pose, occlusion, and resolution continue to confound matchers, there have been significant advances made in face recognition technology to assist law enforcement agencies in their investigations.