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Case Study Facial Recognition Technology and Boston Bombing Suspects

Facial Recognition Technology

A Case Study on Unconstrained Facial Recognition Using the Boston Marathon Bombings Suspects
Researchers at Michigan State University simulate the identification scenario presented by the investigation using two state-of-the-art commercial face recognition systems. The experimental results show one instance where a commercial face matcher returns a rank-one hit for suspect Dzhokhar Tsarnaev against a one million mug shot 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 investigations.

To read the report, click here.

What is the technology and how does it work?

Facial recognition is a type of biometric software application that can identify a specific individual in a digital image by analyzing and comparing patterns. Facial recognition technology is commonly used for security purposes but has increasingly been used in a variety of other applications. The Kinect motion gaming system, for example, uses facial recognition to differentiate among players.

Law Enforcement can implement aspects of this technology to address the advanced security concerns. The FBI, NYPD and DHS have already launched pilot programs of their own with this technology and more agencies are expected to follow suit.



From The Police Chief, vol. LXXX, no. 10, October 2013. Copyright held by the International Association of Chiefs of Police, 515 North Washington Street, Alexandria, VA 22314 USA.

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