‘VeriLook’ Face ID Software Available - GovernmentVideo.com

‘VeriLook’ Face ID Software Available

Surveillance 2.0 uses live video streams from single or multiple high-resolution digital surveillance cameras to provide real-time identification of faces.
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Neurotechnology, a provider of biometric identification technologies, says VeriLook Surveillance 2.0—a software development kit for biometric face identification—is available.

VeriLook Surveillance 2.0 uses live video streams from single or multiple high-resolution digital surveillance cameras to provide real-time identification of faces, Neurotechnology says. VeriLook can be used in a wide range of surveillance systems for retail and commercial areas, entrance monitoring and counting, automated time-attendance systems, law enforcement applications and transportation security, the company says.

The new, integrated face-tracking algorithm in VeriLook Surveillance 2.0 includes a face model that can adapt to visual appearance changes as subjects move across the scene, the company says. The face model continues tracking subjects even when their faces briefly disappear from the frame or when they are partially blocked by other objects or even other faces (a common problem while tracking multiple faces). Because it can now simultaneously process video streams from multiple surveillance cameras, VeriLook Surveillance 2.0 is suitable for use in large surveillance systems, Neurotechnology says.

“VeriLook Surveillance 2.0 SDK now tracks faces with higher tolerance for lighting conditions, face poses and occlusions in multiple live video streams simultaneously,” said Justas Kranauskas, Neurotechnology’s project leader. “Together with real-time face recognition, automatic watch-list synchronization, flexible operator alerts and event logging implementation, VeriLook Surveillance adds value to any video surveillance application,” he said.

VeriLook Surveillance 2.0 incorporates the VeriLook 5.1 face recognition algorithm, which enables detection of faces with up to 45 degrees out-of-plane rotation in yaw angle, Neurotechnology says. The new face tracking algorithm uses motion prediction models to re-localize faces that have undergone full occlusion, such as when a subject has been fully obstructed by a wall and emerged on the other side.

The face model allows the system to efficiently and reliably track faces in front of complex backgrounds and ensures that subjects can be localized in all video frames, even under strenuous conditions, and face images can then be matched against internal databases, such as criminal watch lists or authorized personnel. VeriLook Surveillance will immediately report recognized faces to the system.

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