Smile because you really are on candid camera.
The rapid growth in surveillance cameras is resulting in millions of face images and videos captured every day. The ability to quickly and accurately search all these images to assist in identifying criminal and terrorism suspects is an incredibly important and complex task that can result in safer communities across the globe.
Michigan State University is supporting this effort by licensing its large-scale face-search system developed by biometrics expert Anil Jain, MSU Distinguished Professor of computer science and engineering; Dayong Wang, an MSU postdoctoral fellow; and Charles Otto, an MSU Ph.D. student.
MSU’s automatic face-search system uses a photo from a surveillance camera or crime-scene image to quickly retrieve a list of potential suspects by searching a large database of face images and finding the closest match.
“The strength of this face-search system is that it can process and search so-called ‘faces in the wild’ — unconstrained images,” Jain said. “Unconstrained images are those captured in everyday life that have varied poses, lighting and backgrounds that can make facial recognition challenging. When integrated with a commercial algorithm like NEC Neoface, we achieve even greater accuracy in matching unconstrained face images.
“In fact, we tested this retrieval system on actual photos from law-enforcement video of the Boston Marathon bombing. We found a match of Dzokhar Tsarnaev, the younger brother, at rank-1 among 5 million photos.”
To make the large-scale face-search system available for deployment, MSU has licensed it to NEC Corp. of America, one of the largest providers of biometric technology to law enforcement and commercial entities.
“NEC is committed to maintain its leadership position in facial recognition solutions,” said Raffie Beroukhim, vice president, NECAM’s Biometrics Solutions Division. “In addition to our own continued research, partnerships with academia, in particular Michigan State University, is an important aspect of this commitment. We look forward to the fusion of MSU large-scale face-search algorithm with our industry-leading Neoface facial algorithms to offer more compelling solutions to address ever-increasing security threats and enhance public and national security.”
The licensing of the face-search system is just one example of how MSU innovations put knowledge and research discoveries to work to make communities safer.