Facial recognition software used to make arrest

Using facial-recognition software called NeoFace, investigators in Chicago were able to identify and arrest a suspected mugger by running a single image of the suspect captured on a surveillance camera through the program.

In cities like Chicago, where there are 24,000 surveillance cameras tied into the city’s computer network, facial recognition software like NeoFace could prove to be quite useful. NeoFace, which is being used by law enforcement departments across the United States, enables mug shot browsing, searching, uploading, matching, filtering, and mind-mapping via web-based software. Matching can be performed quickly by uploading local files or via remote devices like phones or wireless video servers.

NeoFace features a generalized learning vector quantization algorithm-based multiple matching face detection technology. Its facial recognition is based on neural network technology and features head, face, and eye position detection and can match an image even when part of the subject’s face might be hidden by a hat or sunglasses, or if the subject’s head is turned, according to the Chicago Sun Times. Specifically, NEC Corporation says that its NeoFace technology provides recognition regardless of vantage point and facial changes, and allows for extraction of similar facial areas.

It also features flexible integration into many types of video monitoring systems, supports various graphic and video formats as well as live cameras, and also supports infrared cameras.

The Chicago police department has been equipped with NeoFace work stations and is now training officers to use the system.

View more information on NeoFace.

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