If you’re a fan of any of the detective shows available on television and streaming services, you’ve probably seen an episode or two where a crucial part of solving the fictional crime is using face-recognition software to identify potential suspects. It’s the digital version of an old-fashioned police lineup. The scenario usually involves detectives finding an old photo or obtaining some grainy security camera footage of a suspect. They turn it over to a colleague in a crime lab, where the photograph or video is quickly processed to identify the subject.
While it may not work exactly as seen in the movies or on a television crime drama, this type of digital matching technology is very real and in use today. With more people having camera equipped cell phones and individuals and business installing surveillance cameras, the amount of available video evidence that can be used to solve crimes has greatly increased. Not having the ability to leverage security video footage and photo evidence can be costly and time consuming for law enforcement departments with limited resources and heavy case loads.
NEC’s Advanced Recognition Systems (ARS) group has a long history of providing the latest biometrics technology to government customers like our NeoFace® Reveal software, NEC’s high-speed matching facial recognition system. When it was independently evaluated by the National Institute of Standards and Technology (NIST), part of the U.S. Department of Commerce, NEC’s NeoFace® algorithm achieved the highest performance evaluation as the most accurate face recognition solution on the market for “one-to-many” video searching.
Watch the video to see how NEC’s ARS group worked with the City of Irving Police Department on a deployment of NEC’s NeoFace® Reveal facial recognition software, which has resulted in high success rates in providing fast, accurate suspect identification intelligence. It has led to increased public safety and decreases in departmental costs by saving detective man hours and reducing the need for added personnel.
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